Structured vocabularies describing concepts from the fields of biology and relationships between concepts.
A specified list of terms with a fixed and unalterable meaning, and from which a selection is made when CATALOGING; ABSTRACTING AND INDEXING; or searching BOOKS; JOURNALS AS TOPIC; and other documents. The control is intended to avoid the scattering of related subjects under different headings (SUBJECT HEADINGS). The list may be altered or extended only by the publisher or issuing agency. (From Harrod's Librarians' Glossary, 7th ed, p163)
Organized activities related to the storage, location, search, and retrieval of information.
Sets of structured vocabularies used for describing and categorizing genes, and gene products by their molecular function, involvement in biological processes, and cellular location. These vocabularies and their associations to genes and gene products (Gene Ontology annotations) are generated and curated by the Gene Ontology Consortium.
The terms, expressions, designations, or symbols used in a particular science, discipline, or specialized subject area.
A field of biology concerned with the development of techniques for the collection and manipulation of biological data, and the use of such data to make biological discoveries or predictions. This field encompasses all computational methods and theories for solving biological problems including manipulation of models and datasets.
A branch of biology dealing with the structure of organisms.
Databases devoted to knowledge about specific genes and gene products.
Sequential operating programs and data which instruct the functioning of a digital computer.
Software designed to store, manipulate, manage, and control data for specific uses.
Computer processing of a language with rules that reflect and describe current usage rather than prescribed usage.
The portion of an interactive computer program that issues messages to and receives commands from a user.
The relationships between symbols and their meanings.
The addition of descriptive information about the function or structure of a molecular sequence to its MOLECULAR SEQUENCE DATA record.
The determination of the pattern of genes expressed at the level of GENETIC TRANSCRIPTION, under specific circumstances or in a specific cell.
A loose confederation of computer communication networks around the world. The networks that make up the Internet are connected through several backbone networks. The Internet grew out of the US Government ARPAnet project and was designed to facilitate information exchange.
Extensive collections, reputedly complete, of facts and data garnered from material of a specialized subject area and made available for analysis and application. The collection can be automated by various contemporary methods for retrieval. The concept should be differentiated from DATABASES, BIBLIOGRAPHIC which is restricted to collections of bibliographic references.
The procedures involved in combining separately developed modules, components, or subsystems so that they work together as a complete system. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed)
A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.
Specific languages used to prepare computer programs.
Hybridization of a nucleic acid sample to a very large set of OLIGONUCLEOTIDE PROBES, which have been attached individually in columns and rows to a solid support, to determine a BASE SEQUENCE, or to detect variations in a gene sequence, GENE EXPRESSION, or for GENE MAPPING.
Collections of facts, assumptions, beliefs, and heuristics that are used in combination with databases to achieve desired results, such as a diagnosis, an interpretation, or a solution to a problem (From McGraw Hill Dictionary of Scientific and Technical Terms, 6th ed).
Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment.
Databases containing information about PROTEINS such as AMINO ACID SEQUENCE; PROTEIN CONFORMATION; and other properties.
Systematic organization, storage, retrieval, and dissemination of specialized information, especially of a scientific or technical nature (From ALA Glossary of Library and Information Science, 1983). It often involves authenticating or validating information.
Use of sophisticated analysis tools to sort through, organize, examine, and combine large sets of information.
The systematic study of the complete DNA sequences (GENOME) of organisms.
The systematic arrangement of entities in any field into categories classes based on common characteristics such as properties, morphology, subject matter, etc.
The field of knowledge, theory, and technology dealing with the collection of facts and figures, and the processes and methods involved in their manipulation, storage, dissemination, publication, and retrieval. It includes the fields of COMMUNICATION; PUBLISHING; LIBRARY SCIENCE; and informatics.
Theory and development of COMPUTER SYSTEMS which perform tasks that normally require human intelligence. Such tasks may include speech recognition, LEARNING; VISUAL PERCEPTION; MATHEMATICAL COMPUTING; reasoning, PROBLEM SOLVING, DECISION-MAKING, and translation of language.
A research and development program initiated by the NATIONAL LIBRARY OF MEDICINE to build knowledge sources for the purpose of aiding the development of systems that help health professionals retrieve and integrate biomedical information. The knowledge sources can be used to link disparate information systems to overcome retrieval problems caused by differences in terminology and the scattering of relevant information across many databases. The three knowledge sources are the Metathesaurus, the Semantic Network, and the Specialist Lexicon.
A set of statistical methods used to group variables or observations into strongly inter-related subgroups. In epidemiology, it may be used to analyze a closely grouped series of events or cases of disease or other health-related phenomenon with well-defined distribution patterns in relation to time or place or both.
The pattern of GENE EXPRESSION at the level of genetic transcription in a specific organism or under specific circumstances in specific cells.
Controlled vocabulary of clinical terms produced by the International Health Terminology Standards Development Organisation (IHTSDO).
Linear POLYPEPTIDES that are synthesized on RIBOSOMES and may be further modified, crosslinked, cleaved, or assembled into complex proteins with several subunits. The specific sequence of AMINO ACIDS determines the shape the polypeptide will take, during PROTEIN FOLDING, and the function of the protein.
Partial cDNA (DNA, COMPLEMENTARY) sequences that are unique to the cDNAs from which they were derived.
The process of pictorial communication, between human and computers, in which the computer input and output have the form of charts, drawings, or other appropriate pictorial representation.
Interacting DNA-encoded regulatory subsystems in the GENOME that coordinate input from activator and repressor TRANSCRIPTION FACTORS during development, cell differentiation, or in response to environmental cues. The networks function to ultimately specify expression of particular sets of GENES for specific conditions, times, or locations.
Biological activities and function of the whole organism in human, animal, microorgansims, and plants, and of the biosphere.
One of the BIOLOGICAL SCIENCE DISCIPLINES concerned with the origin, structure, development, growth, function, genetics, and reproduction of animals, plants, and microorganisms.
A bibliographic database that includes MEDLINE as its primary subset. It is produced by the National Center for Biotechnology Information (NCBI), part of the NATIONAL LIBRARY OF MEDICINE. PubMed, which is searchable through NLM's Web site, also includes access to additional citations to selected life sciences journals not in MEDLINE, and links to other resources such as the full-text of articles at participating publishers' Web sites, NCBI's molecular biology databases, and PubMed Central.
Methods for determining interaction between PROTEINS.

Evaluation of research in biomedical ontologies. (1/26)


Towards Web 3.0: taxonomies and ontologies for medical education -- a systematic review. (2/26)


Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers. (3/26)


FYPO: the fission yeast phenotype ontology. (4/26)


Effects of guideline-based training on the quality of formal ontologies: a randomized controlled trial. (5/26)


OntoQuery: easy-to-use web-based OWL querying. (6/26)


The International Mouse Phenotyping Consortium Web Portal, a unified point of access for knockout mice and related phenotyping data. (7/26)


The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data. (8/26)


Biological ontologies are formal representations of knowledge in the biological sciences, which consist of standardized vocabularies and relationships between them. They provide a way to represent and organize complex concepts and relationships in a machine-readable format, enabling computational analysis and integration of diverse biological data. Ontologies can capture various levels of biological organization, from molecular interactions to whole organisms and ecosystems. Examples of widely used biological ontologies include the Gene Ontology (GO) for molecular functions and processes, the Cell Ontology (CL) for cell types, and the Chemical Entities of Biological Interest (ChEBI) ontology for small molecules.

A controlled vocabulary in a medical context refers to a specific set of standardized terms and phrases that are used in clinical documentation and communication. These vocabularies are often created and maintained by professional organizations or governmental bodies to ensure consistency, accuracy, and interoperability in the sharing and retrieval of health information.

Controlled vocabularies can include terminologies such as Systematized Nomenclature of Medicine (SNOMED), International Classification of Diseases (ICD), Logical Observation Identifiers Names and Codes (LOINC), and RxNorm, among others. By using a controlled vocabulary, healthcare providers can more easily share and analyze health data, support clinical decision-making, and facilitate accurate coding and billing.

'Information Storage and Retrieval' in the context of medical informatics refers to the processes and systems used for the recording, storing, organizing, protecting, and retrieving electronic health information (e.g., patient records, clinical data, medical images) for various purposes such as diagnosis, treatment planning, research, and education. This may involve the use of electronic health record (EHR) systems, databases, data warehouses, and other digital technologies that enable healthcare providers to access and share accurate, up-to-date, and relevant information about a patient's health status, medical history, and care plan. The goal is to improve the quality, safety, efficiency, and coordination of healthcare delivery by providing timely and evidence-based information to support clinical decision-making and patient engagement.

Gene Ontology (GO) is not a medical term, but rather a bioinformatics term used to describe a controlled vocabulary or ontology for describing molecular functions, biological processes, and cellular components in which genes and gene products are involved. It provides a standardized way to represent and share information about gene function across different species.

The GO ontology is organized as a directed acyclic graph (DAG), where each term has defined relationships with other terms, allowing for the representation of complex biological concepts. The GO terms can be used to describe molecular functions such as enzymatic activities or binding interactions, biological processes such as metabolic pathways or signal transduction cascades, and cellular components such as organelles or subcellular structures.

GO analysis is a common approach in bioinformatics for interpreting large-scale genomic data, such as microarray or next-generation sequencing experiments, to identify genes that are involved in specific biological processes or molecular functions of interest.

"Terminology as a topic" in the context of medical education and practice refers to the study and use of specialized language and terms within the field of medicine. This includes understanding the meaning, origins, and appropriate usage of medical terminology in order to effectively communicate among healthcare professionals and with patients. It may also involve studying the evolution and cultural significance of medical terminology. The importance of "terminology as a topic" lies in promoting clear and accurate communication, which is essential for providing safe and effective patient care.

Computational biology is a branch of biology that uses mathematical and computational methods to study biological data, models, and processes. It involves the development and application of algorithms, statistical models, and computational approaches to analyze and interpret large-scale molecular and phenotypic data from genomics, transcriptomics, proteomics, metabolomics, and other high-throughput technologies. The goal is to gain insights into biological systems and processes, develop predictive models, and inform experimental design and hypothesis testing in the life sciences. Computational biology encompasses a wide range of disciplines, including bioinformatics, systems biology, computational genomics, network biology, and mathematical modeling of biological systems.

Anatomy is the branch of biology that deals with the study of the structure of organisms and their parts. In medicine, anatomy is the detailed study of the structures of the human body and its organs. It can be divided into several subfields, including:

1. Gross anatomy: Also known as macroscopic anatomy, this is the study of the larger structures of the body, such as the organs and organ systems, using techniques such as dissection and observation.
2. Histology: This is the study of tissues at the microscopic level, including their structure, composition, and function.
3. Embryology: This is the study of the development of the embryo and fetus from conception to birth.
4. Neuroanatomy: This is the study of the structure and organization of the nervous system, including the brain and spinal cord.
5. Comparative anatomy: This is the study of the structures of different species and how they have evolved over time.

Anatomy is a fundamental subject in medical education, as it provides the basis for understanding the function of the human body and the underlying causes of disease.

A genetic database is a type of biomedical or health informatics database that stores and organizes genetic data, such as DNA sequences, gene maps, genotypes, haplotypes, and phenotype information. These databases can be used for various purposes, including research, clinical diagnosis, and personalized medicine.

There are different types of genetic databases, including:

1. Genomic databases: These databases store whole genome sequences, gene expression data, and other genomic information. Examples include the National Center for Biotechnology Information's (NCBI) GenBank, the European Nucleotide Archive (ENA), and the DNA Data Bank of Japan (DDBJ).
2. Gene databases: These databases contain information about specific genes, including their location, function, regulation, and evolution. Examples include the Online Mendelian Inheritance in Man (OMIM) database, the Universal Protein Resource (UniProt), and the Gene Ontology (GO) database.
3. Variant databases: These databases store information about genetic variants, such as single nucleotide polymorphisms (SNPs), insertions/deletions (INDELs), and copy number variations (CNVs). Examples include the Database of Single Nucleotide Polymorphisms (dbSNP), the Catalogue of Somatic Mutations in Cancer (COSMIC), and the International HapMap Project.
4. Clinical databases: These databases contain genetic and clinical information about patients, such as their genotype, phenotype, family history, and response to treatments. Examples include the ClinVar database, the Pharmacogenomics Knowledgebase (PharmGKB), and the Genetic Testing Registry (GTR).
5. Population databases: These databases store genetic information about different populations, including their ancestry, demographics, and genetic diversity. Examples include the 1000 Genomes Project, the Human Genome Diversity Project (HGDP), and the Allele Frequency Net Database (AFND).

Genetic databases can be publicly accessible or restricted to authorized users, depending on their purpose and content. They play a crucial role in advancing our understanding of genetics and genomics, as well as improving healthcare and personalized medicine.

I am not aware of a widely accepted medical definition for the term "software," as it is more commonly used in the context of computer science and technology. Software refers to programs, data, and instructions that are used by computers to perform various tasks. It does not have direct relevance to medical fields such as anatomy, physiology, or clinical practice. If you have any questions related to medicine or healthcare, I would be happy to try to help with those instead!

A Database Management System (DBMS) is a software application that enables users to define, create, maintain, and manipulate databases. It provides a structured way to organize, store, retrieve, and manage data in a digital format. The DBMS serves as an interface between the database and the applications or users that access it, allowing for standardized interactions and data access methods. Common functions of a DBMS include data definition, data manipulation, data security, data recovery, and concurrent data access control. Examples of DBMS include MySQL, Oracle, Microsoft SQL Server, and MongoDB.

I'm sorry for any confusion, but "Natural Language Processing" (NLP) is actually a subfield of artificial intelligence that focuses on the interaction between computers and human language. It involves developing algorithms and software to understand, interpret, and generate human language in a valuable way.

In a medical context, NLP can be used to analyze electronic health records, clinical notes, and other forms of medical documentation to extract meaningful information, support clinical decision-making, and improve patient care. For example, NLP can help identify patients at risk for certain conditions, monitor treatment responses, and detect adverse drug events.

However, NLP is not a medical term or concept itself, so it doesn't have a specific medical definition.

A User-Computer Interface (also known as Human-Computer Interaction) refers to the point at which a person (user) interacts with a computer system. This can include both hardware and software components, such as keyboards, mice, touchscreens, and graphical user interfaces (GUIs). The design of the user-computer interface is crucial in determining the usability and accessibility of a computer system for the user. A well-designed interface should be intuitive, efficient, and easy to use, minimizing the cognitive load on the user and allowing them to effectively accomplish their tasks.

I'm sorry for any confusion, but "semantics" is not a term that has a specific medical definition. Semantics is actually a branch of linguistics that deals with the study of meaning, reference, and the interpretation of signs and symbols, either individually or in combination. It is used in various fields including computer science, anthropology, psychology, and philosophy.

However, if you have any medical terms or concepts that you would like me to explain, I'd be happy to help!

Molecular sequence annotation is the process of identifying and describing the characteristics, functional elements, and relevant information of a DNA, RNA, or protein sequence at the molecular level. This process involves marking the location and function of various features such as genes, regulatory regions, coding and non-coding sequences, intron-exon boundaries, promoters, introns, untranslated regions (UTRs), binding sites for proteins or other molecules, and post-translational modifications in a given molecular sequence.

The annotation can be manual, where experts curate and analyze the data to predict features based on biological knowledge and experimental evidence. Alternatively, computational methods using various bioinformatics tools and algorithms can be employed for automated annotation. These tools often rely on comparative analysis, pattern recognition, and machine learning techniques to identify conserved sequence patterns, motifs, or domains that are associated with specific functions.

The annotated molecular sequences serve as valuable resources in genomic and proteomic studies, contributing to the understanding of gene function, evolutionary relationships, disease associations, and biotechnological applications.

Gene expression profiling is a laboratory technique used to measure the activity (expression) of thousands of genes at once. This technique allows researchers and clinicians to identify which genes are turned on or off in a particular cell, tissue, or organism under specific conditions, such as during health, disease, development, or in response to various treatments.

The process typically involves isolating RNA from the cells or tissues of interest, converting it into complementary DNA (cDNA), and then using microarray or high-throughput sequencing technologies to determine which genes are expressed and at what levels. The resulting data can be used to identify patterns of gene expression that are associated with specific biological states or processes, providing valuable insights into the underlying molecular mechanisms of diseases and potential targets for therapeutic intervention.

In recent years, gene expression profiling has become an essential tool in various fields, including cancer research, drug discovery, and personalized medicine, where it is used to identify biomarkers of disease, predict patient outcomes, and guide treatment decisions.

I'm sorry for any confusion, but "Internet" is a term that pertains to the global network of interconnected computers and servers that enable the transmission and reception of data via the internet protocol (IP). It is not a medical term and does not have a specific medical definition. If you have any questions related to medicine or health, I'd be happy to try to help answer them for you!

A factual database in the medical context is a collection of organized and structured data that contains verified and accurate information related to medicine, healthcare, or health sciences. These databases serve as reliable resources for various stakeholders, including healthcare professionals, researchers, students, and patients, to access evidence-based information for making informed decisions and enhancing knowledge.

Examples of factual medical databases include:

1. PubMed: A comprehensive database of biomedical literature maintained by the US National Library of Medicine (NLM). It contains citations and abstracts from life sciences journals, books, and conference proceedings.
2. MEDLINE: A subset of PubMed, MEDLINE focuses on high-quality, peer-reviewed articles related to biomedicine and health. It is the primary component of the NLM's database and serves as a critical resource for healthcare professionals and researchers worldwide.
3. Cochrane Library: A collection of systematic reviews and meta-analyses focused on evidence-based medicine. The library aims to provide unbiased, high-quality information to support clinical decision-making and improve patient outcomes.
4. OVID: A platform that offers access to various medical and healthcare databases, including MEDLINE, Embase, and PsycINFO. It facilitates the search and retrieval of relevant literature for researchers, clinicians, and students.
5. A registry and results database of publicly and privately supported clinical studies conducted around the world. The platform aims to increase transparency and accessibility of clinical trial data for healthcare professionals, researchers, and patients.
6. UpToDate: An evidence-based, physician-authored clinical decision support resource that provides information on diagnosis, treatment, and prevention of medical conditions. It serves as a point-of-care tool for healthcare professionals to make informed decisions and improve patient care.
7. TRIP Database: A search engine designed to facilitate evidence-based medicine by providing quick access to high-quality resources, including systematic reviews, clinical guidelines, and practice recommendations.
8. National Guideline Clearinghouse (NGC): A database of evidence-based clinical practice guidelines and related documents developed through a rigorous review process. The NGC aims to provide clinicians, healthcare providers, and policymakers with reliable guidance for patient care.
9. DrugBank: A comprehensive, freely accessible online database containing detailed information about drugs, their mechanisms, interactions, and targets. It serves as a valuable resource for researchers, healthcare professionals, and students in the field of pharmacology and drug discovery.
10. Genetic Testing Registry (GTR): A database that provides centralized information about genetic tests, test developers, laboratories offering tests, and clinical validity and utility of genetic tests. It serves as a resource for healthcare professionals, researchers, and patients to make informed decisions regarding genetic testing.

I'm sorry for any confusion, but "Systems Integration" is not a medical term per se. It is a term more commonly used in the fields of engineering, computer science, and information technology. However, I can provide you with a general definition:

Systems Integration refers to the process of combining different sub-systems or components into a single, cohesive system to allow seamless communication and data exchange between them. This integration aims to improve efficiency, performance, and overall functionality by unifying various standalone systems into an interconnected network that behaves as a unified whole.

In the context of healthcare, systems integration can be applied to merge different electronic health record (EHR) systems, medical devices, or other healthcare technologies to create a comprehensive, interoperable healthcare information system. This facilitates better care coordination, data sharing, and decision-making among healthcare providers, ultimately enhancing patient outcomes and satisfaction.

An algorithm is not a medical term, but rather a concept from computer science and mathematics. In the context of medicine, algorithms are often used to describe step-by-step procedures for diagnosing or managing medical conditions. These procedures typically involve a series of rules or decision points that help healthcare professionals make informed decisions about patient care.

For example, an algorithm for diagnosing a particular type of heart disease might involve taking a patient's medical history, performing a physical exam, ordering certain diagnostic tests, and interpreting the results in a specific way. By following this algorithm, healthcare professionals can ensure that they are using a consistent and evidence-based approach to making a diagnosis.

Algorithms can also be used to guide treatment decisions. For instance, an algorithm for managing diabetes might involve setting target blood sugar levels, recommending certain medications or lifestyle changes based on the patient's individual needs, and monitoring the patient's response to treatment over time.

Overall, algorithms are valuable tools in medicine because they help standardize clinical decision-making and ensure that patients receive high-quality care based on the latest scientific evidence.

I'm afraid there seems to be a misunderstanding. Programming languages are a field of study in computer science and are not related to medicine. They are used to create computer programs, through the composition of symbols and words. Some popular programming languages include Python, Java, C++, and JavaScript. If you have any questions about programming or computer science, I'd be happy to try and help answer them!

Oligonucleotide Array Sequence Analysis is a type of microarray analysis that allows for the simultaneous measurement of the expression levels of thousands of genes in a single sample. In this technique, oligonucleotides (short DNA sequences) are attached to a solid support, such as a glass slide, in a specific pattern. These oligonucleotides are designed to be complementary to specific target mRNA sequences from the sample being analyzed.

During the analysis, labeled RNA or cDNA from the sample is hybridized to the oligonucleotide array. The level of hybridization is then measured and used to determine the relative abundance of each target sequence in the sample. This information can be used to identify differences in gene expression between samples, which can help researchers understand the underlying biological processes involved in various diseases or developmental stages.

It's important to note that this technique requires specialized equipment and bioinformatics tools for data analysis, as well as careful experimental design and validation to ensure accurate and reproducible results.

I'm sorry for any confusion, but "knowledge bases" is a general term that refers to structured collections of knowledge in a specific field or area, and it is not a medical term with a defined meaning in the medical field. Knowledge bases can be found in many fields, including medicine, and they typically take the form of databases or repositories of information that are used to store, organize, and retrieve knowledge. In the medical field, knowledge bases might include information about diseases, treatments, medications, and other medical topics. They can be used by healthcare professionals, researchers, and patients to access accurate and reliable information.

Biological models, also known as physiological models or organismal models, are simplified representations of biological systems, processes, or mechanisms that are used to understand and explain the underlying principles and relationships. These models can be theoretical (conceptual or mathematical) or physical (such as anatomical models, cell cultures, or animal models). They are widely used in biomedical research to study various phenomena, including disease pathophysiology, drug action, and therapeutic interventions.

Examples of biological models include:

1. Mathematical models: These use mathematical equations and formulas to describe complex biological systems or processes, such as population dynamics, metabolic pathways, or gene regulation networks. They can help predict the behavior of these systems under different conditions and test hypotheses about their underlying mechanisms.
2. Cell cultures: These are collections of cells grown in a controlled environment, typically in a laboratory dish or flask. They can be used to study cellular processes, such as signal transduction, gene expression, or metabolism, and to test the effects of drugs or other treatments on these processes.
3. Animal models: These are living organisms, usually vertebrates like mice, rats, or non-human primates, that are used to study various aspects of human biology and disease. They can provide valuable insights into the pathophysiology of diseases, the mechanisms of drug action, and the safety and efficacy of new therapies.
4. Anatomical models: These are physical representations of biological structures or systems, such as plastic models of organs or tissues, that can be used for educational purposes or to plan surgical procedures. They can also serve as a basis for developing more sophisticated models, such as computer simulations or 3D-printed replicas.

Overall, biological models play a crucial role in advancing our understanding of biology and medicine, helping to identify new targets for therapeutic intervention, develop novel drugs and treatments, and improve human health.

A protein database is a type of biological database that contains information about proteins and their structures, functions, sequences, and interactions with other molecules. These databases can include experimentally determined data, such as protein sequences derived from DNA sequencing or mass spectrometry, as well as predicted data based on computational methods.

Some examples of protein databases include:

1. UniProtKB: a comprehensive protein database that provides information about protein sequences, functions, and structures, as well as literature references and links to other resources.
2. PDB (Protein Data Bank): a database of three-dimensional protein structures determined by experimental methods such as X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy.
3. BLAST (Basic Local Alignment Search Tool): a web-based tool that allows users to compare a query protein sequence against a protein database to identify similar sequences and potential functional relationships.
4. InterPro: a database of protein families, domains, and functional sites that provides information about protein function based on sequence analysis and other data.
5. STRING (Search Tool for the Retrieval of Interacting Genes/Proteins): a database of known and predicted protein-protein interactions, including physical and functional associations.

Protein databases are essential tools in proteomics research, enabling researchers to study protein function, evolution, and interaction networks on a large scale.

In a medical context, documentation refers to the process of recording and maintaining written or electronic records of a patient's health status, medical history, treatment plans, medications, and other relevant information. The purpose of medical documentation is to provide clear and accurate communication among healthcare providers, to support clinical decision-making, to ensure continuity of care, to meet legal and regulatory requirements, and to facilitate research and quality improvement initiatives.

Medical documentation typically includes various types of records such as:

1. Patient's demographic information, including name, date of birth, gender, and contact details.
2. Medical history, including past illnesses, surgeries, allergies, and family medical history.
3. Physical examination findings, laboratory and diagnostic test results, and diagnoses.
4. Treatment plans, including medications, therapies, procedures, and follow-up care.
5. Progress notes, which document the patient's response to treatment and any changes in their condition over time.
6. Consultation notes, which record communication between healthcare providers regarding a patient's care.
7. Discharge summaries, which provide an overview of the patient's hospital stay, including diagnoses, treatments, and follow-up plans.

Medical documentation must be clear, concise, accurate, and timely, and it should adhere to legal and ethical standards. Healthcare providers are responsible for maintaining the confidentiality of patients' medical records and ensuring that they are accessible only to authorized personnel.

Data mining, in the context of health informatics and medical research, refers to the process of discovering patterns, correlations, and insights within large sets of patient or clinical data. It involves the use of advanced analytical techniques such as machine learning algorithms, statistical models, and artificial intelligence to identify and extract useful information from complex datasets.

The goal of data mining in healthcare is to support evidence-based decision making, improve patient outcomes, and optimize resource utilization. Applications of data mining in healthcare include predicting disease outbreaks, identifying high-risk patients, personalizing treatment plans, improving clinical workflows, and detecting fraud and abuse in healthcare systems.

Data mining can be performed on various types of healthcare data, including electronic health records (EHRs), medical claims databases, genomic data, imaging data, and sensor data from wearable devices. However, it is important to ensure that data mining techniques are used ethically and responsibly, with appropriate safeguards in place to protect patient privacy and confidentiality.

Genomics is the scientific study of genes and their functions. It involves the sequencing and analysis of an organism's genome, which is its complete set of DNA, including all of its genes. Genomics also includes the study of how genes interact with each other and with the environment. This field of study can provide important insights into the genetic basis of diseases and can lead to the development of new diagnostic tools and treatments.

In the context of medicine, classification refers to the process of categorizing or organizing diseases, disorders, injuries, or other health conditions based on their characteristics, symptoms, causes, or other factors. This helps healthcare professionals to understand, diagnose, and treat various medical conditions more effectively.

There are several well-known classification systems in medicine, such as:

1. The International Classification of Diseases (ICD) - developed by the World Health Organization (WHO), it is used worldwide for mortality and morbidity statistics, reimbursement systems, and automated decision support in health care. This system includes codes for diseases, signs and symptoms, abnormal findings, social circumstances, and external causes of injury or diseases.
2. The Diagnostic and Statistical Manual of Mental Disorders (DSM) - published by the American Psychiatric Association, it provides a standardized classification system for mental health disorders to improve communication between mental health professionals, facilitate research, and guide treatment.
3. The International Classification of Functioning, Disability and Health (ICF) - developed by the WHO, this system focuses on an individual's functioning and disability rather than solely on their medical condition. It covers body functions and structures, activities, and participation, as well as environmental and personal factors that influence a person's life.
4. The TNM Classification of Malignant Tumors - created by the Union for International Cancer Control (UICC), it is used to describe the anatomical extent of cancer, including the size of the primary tumor (T), involvement of regional lymph nodes (N), and distant metastasis (M).

These classification systems help medical professionals communicate more effectively about patients' conditions, make informed treatment decisions, and track disease trends over time.

I'm sorry for any confusion, but "Information Science" is not a term that has a specific medical definition. Information science is a multidisciplinary field that deals with the study, management, and analysis of information, its representation, processing, dissemination, and retrieval in various contexts, including libraries, databases, data analytics, knowledge management, and intellectual property rights.

While information science may not have a direct medical definition, it does have important applications in healthcare and medicine, such as in the areas of clinical decision support systems, electronic health records, biomedical informatics, public health surveillance, and evidence-based medicine. These applications involve the use of advanced technologies and methods to analyze large volumes of data, extract meaningful insights, and support better clinical outcomes.

Artificial Intelligence (AI) in the medical context refers to the simulation of human intelligence processes by machines, particularly computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction.

In healthcare, AI is increasingly being used to analyze large amounts of data, identify patterns, make decisions, and perform tasks that would normally require human intelligence. This can include tasks such as diagnosing diseases, recommending treatments, personalizing patient care, and improving clinical workflows.

Examples of AI in medicine include machine learning algorithms that analyze medical images to detect signs of disease, natural language processing tools that extract relevant information from electronic health records, and robot-assisted surgery systems that enable more precise and minimally invasive procedures.

The Unified Medical Language System (UMLS) is a set of files and software developed by the U.S. National Library of Medicine (NLM). It provides a comprehensive source of biomedical and health-related terms aimed at unifying and standardizing the language used in various areas of the medical field, such as clinical care, research, and education.

The UMLS includes many different vocabularies, classifications, and coding systems, including but not limited to:

* Systematized Nomenclature of Medicine--Clinical Terms (SNOMED CT)
* International Classification of Diseases (ICD)
* Current Procedural Terminology (CPT)
* Logical Observation Identifiers Names and Codes (LOINC)

By integrating these various terminologies, the UMLS enables more effective searching, information retrieval, and data analysis across different systems and databases. It also supports natural language processing (NLP) applications, such as text mining and clinical decision support systems.

Cluster analysis is a statistical method used to group similar objects or data points together based on their characteristics or features. In medical and healthcare research, cluster analysis can be used to identify patterns or relationships within complex datasets, such as patient records or genetic information. This technique can help researchers to classify patients into distinct subgroups based on their symptoms, diagnoses, or other variables, which can inform more personalized treatment plans or public health interventions.

Cluster analysis involves several steps, including:

1. Data preparation: The researcher must first collect and clean the data, ensuring that it is complete and free from errors. This may involve removing outlier values or missing data points.
2. Distance measurement: Next, the researcher must determine how to measure the distance between each pair of data points. Common methods include Euclidean distance (the straight-line distance between two points) or Manhattan distance (the distance between two points along a grid).
3. Clustering algorithm: The researcher then applies a clustering algorithm, which groups similar data points together based on their distances from one another. Common algorithms include hierarchical clustering (which creates a tree-like structure of clusters) or k-means clustering (which assigns each data point to the nearest centroid).
4. Validation: Finally, the researcher must validate the results of the cluster analysis by evaluating the stability and robustness of the clusters. This may involve re-running the analysis with different distance measures or clustering algorithms, or comparing the results to external criteria.

Cluster analysis is a powerful tool for identifying patterns and relationships within complex datasets, but it requires careful consideration of the data preparation, distance measurement, and validation steps to ensure accurate and meaningful results.

The transcriptome refers to the complete set of RNA molecules, including messenger RNA (mRNA), ribosomal RNA (rRNA), transfer RNA (tRNA), and other non-coding RNAs, that are present in a cell or a population of cells at a given point in time. It reflects the genetic activity and provides information about which genes are being actively transcribed and to what extent. The transcriptome can vary under different conditions, such as during development, in response to environmental stimuli, or in various diseases, making it an important area of study in molecular biology and personalized medicine.

The Systematized Nomenclature of Medicine (SNOMED) is a systematically organized collection of medical terms that are used to describe medical diagnoses, findings, procedures, and other health-related concepts. It is a standardized terminology that is widely adopted in the field of healthcare and clinical research to facilitate accurate and consistent exchange of health information among different healthcare providers, institutions, and electronic health records (EHRs) systems.

SNOMED is designed to capture detailed clinical data and support effective clinical decision-making by providing a common language for describing and sharing clinical information. It includes over 350,000 concepts that are organized into hierarchies based on their relationships to each other. The hierarchical structure of SNOMED allows users to navigate through the terminology and find the most specific concept that describes a particular clinical phenomenon.

SNOMED is maintained by the International Health Terminology Standards Development Organization (IHTSDO), which is responsible for updating and expanding the terminology to reflect changes in medical knowledge and practice. SNOMED is used in many countries around the world, including the United States, Canada, Australia, and several European countries.

Proteins are complex, large molecules that play critical roles in the body's functions. They are made up of amino acids, which are organic compounds that are the building blocks of proteins. Proteins are required for the structure, function, and regulation of the body's tissues and organs. They are essential for the growth, repair, and maintenance of body tissues, and they play a crucial role in many biological processes, including metabolism, immune response, and cellular signaling. Proteins can be classified into different types based on their structure and function, such as enzymes, hormones, antibodies, and structural proteins. They are found in various foods, especially animal-derived products like meat, dairy, and eggs, as well as plant-based sources like beans, nuts, and grains.

Expressed Sequence Tags (ESTs) are short, single-pass DNA sequences that are derived from cDNA libraries. They represent a quick and cost-effective method for large-scale sequencing of gene transcripts and provide an unbiased view of the genes being actively expressed in a particular tissue or developmental stage. ESTs can be used to identify and study new genes, to analyze patterns of gene expression, and to develop molecular markers for genetic mapping and genome analysis.

Computer graphics is the field of study and practice related to creating images and visual content using computer technology. It involves various techniques, algorithms, and tools for generating, manipulating, and rendering digital images and models. These can include 2D and 3D modeling, animation, rendering, visualization, and image processing. Computer graphics is used in a wide range of applications, including video games, movies, scientific simulations, medical imaging, architectural design, and data visualization.

Gene Regulatory Networks (GRNs) are complex systems of molecular interactions that regulate the expression of genes within an organism. These networks consist of various types of regulatory elements, including transcription factors, enhancers, promoters, and silencers, which work together to control when, where, and to what extent a gene is expressed.

In GRNs, transcription factors bind to specific DNA sequences in the regulatory regions of target genes, either activating or repressing their transcription into messenger RNA (mRNA). This process is influenced by various intracellular and extracellular signals that modulate the activity of transcription factors, allowing for precise regulation of gene expression in response to changing environmental conditions.

The structure and behavior of GRNs can be represented as a network of nodes (genes) and edges (regulatory interactions), with the strength and directionality of these interactions determined by the specific molecular mechanisms involved. Understanding the organization and dynamics of GRNs is crucial for elucidating the underlying causes of various biological processes, including development, differentiation, homeostasis, and disease.

Biological processes refer to the series of interactions and reactions that occur within a living organism in order to maintain life. These processes are often complex and involve multiple systems and structures within the body. They can include things like metabolism, cell division, growth and development, respiration, circulation, immune response, and digestion, among others.

Biological processes are typically regulated by a combination of genetic and environmental factors, and they can be influenced by various internal and external stimuli. The study of biological processes is a key area of focus in the field of biology, as understanding these processes can shed light on how living organisms function, grow, reproduce, and respond to changes in their environment.

In medical terms, understanding biological processes is essential for developing effective treatments for various diseases and conditions. By studying the underlying mechanisms that contribute to disease, researchers can identify potential targets for therapeutic intervention and develop new drugs or other treatments designed to modulate specific biological processes.

Biology is the scientific study of living organisms and their vital processes. It deals with the characteristics, classification, and behaviors of plants, animals, and microorganisms, as well as how they interact with each other and the environment. Biology covers a wide range of topics, including genetics, cell biology, evolution, ecology, and physiology. The goal of biological research is to understand the fundamental principles that govern the functioning of living systems and to apply this knowledge to improve human health, agriculture, and the environment.

PubMed is not a medical condition or term, but rather a biomedical literature search engine and database maintained by the National Center for Biotechnology Information (NCBI), a division of the U.S. National Library of Medicine (NLM). It provides access to life sciences literature, including journal articles in medicine, nursing, dentistry, veterinary medicine, health care systems, and preclinical sciences.

PubMed contains more than 30 million citations and abstracts from MEDLINE, life science journals, and online books. Many of the citations include links to full-text articles on publishers' websites or through NCBI's DocSumo service. Researchers, healthcare professionals, students, and the general public use PubMed to find relevant and reliable information in the biomedical literature for research, education, and patient care purposes.

Protein interaction mapping is a research approach used to identify and characterize the physical interactions between different proteins within a cell or organism. This process often involves the use of high-throughput experimental techniques, such as yeast two-hybrid screening, mass spectrometry-based approaches, or protein fragment complementation assays, to detect and quantify the binding affinities of protein pairs. The resulting data is then used to construct a protein interaction network, which can provide insights into functional relationships between proteins, help elucidate cellular pathways, and inform our understanding of biological processes in health and disease.

OBO-Edit, an ontology browser for most of the Open Biological and Biomedical Ontologies OBO Foundry, a suite of interoperable ... "Ontology browser for most of the Open Biological and Biomedical Ontologies". Berkeley Bioinformatics Open Source Project (BBOP ... Folksonomy Formal concept analysis Formal ontology Knowledge graph Lattice Ontology Ontology alignment Ontology chart Open ... The Gellish ontology is an example of a combination of an upper and a domain ontology. A survey of ontology visualization ... (Use dmy dates from December 2015, Biological databases, Ontology (information science), Design of ... Experimental factor ontology, also known as EFO, is an open-access ontology of experimental variables particularly those used ... EFO makes use of existing biomedical ontologies from the Open Biomedical Ontologies collection in order to improve ... European Molecular Biology Laboratory Gene ontology Open Biomedical Ontologies Malone, J.; Holloway, E.; Adamusiak, T.; ...
... an introduction to the biological collections ontology and related ontologies". PLOS ONE. 9 (3): e89606. Bibcode:2014PLoSO... ... Zheng J, Harris MR, Masci AM, Lin Y, Hero A, Smith B, He Y (September 2016). "The Ontology of Biological and Clinical ... Gaudet P, Williams JG, Fey P, Chisholm RL (March 2008). "An anatomy ontology to represent biological knowledge in Dictyostelium ... Buttigieg PL, Morrison N, Smith B, Mungall CJ, Lewis SE (December 2013). "The environment ontology: contextualising biological ...
The Sequence Ontology (SO) is an ontology suitable for describing biological sequences. It is designed to make the naming of ... Articles with short description, Short description is different from Wikidata, Ontology (information science), Biological ... Eilbeck K, Lewis SE, Mungall CJ, Yandell M, Stein L, Durbin R, Ashburner M (2005). "The Sequence Ontology: a tool for the ... Mungall CJ, Batchelor C, Eilbeck K (Feb 2011). "Evolution of the Sequence Ontology terms and relationships". Journal of ...
It is part of the Open Biomedical and Biological Ontologies (OBO) Foundry. The Cell Ontology identifiers and organizational ... The Cell Ontology was first described in an academic article in 2005. Gene ontology OBO Foundry Diehl AD, Meehan TF, Bradford ... The Cell Ontology is an ontology that aims at capturing the diversity of cell types in animals. ... Cell Ontology GitHub page v t e (Ontology (information science), All stub articles, Biology stubs). ...
... the Plant Ontology, the Information Artifact Ontology, and the Biological Collections Ontology. The basic structure of the PPO ... An Introduction to the Biological Collections Ontology and Related Ontologies". PLOS ONE. 9 (3): e89606. Bibcode:2014PLoSO... ... Plant Ontology anatomy terms were used to enable the ontology to infer the presence or absence of hierarchical phenological ... The Plant Phenology Ontology (PPO) is a collection of OBO Foundry ontologies that facilitate integration of heterogeneous data ...
The rise of Systems Biology, seeking to comprehend biological processes as a whole, highlighted the need to not only develop ... The Systems Biology Ontology (SBO) is a set of controlled, relational vocabularies of terms commonly used in systems biology, ... The development of the ontology was announced more officially in a message from Le Novère to Michael Hucka and Andrew Finney on ... The Systems Biology Pathway Exchange (SBPAX) allows SBO terms to be added to Biological Pathway Exchange (BioPAX). This links ...
Chicco, Davide; Masseroli, Marco (2019). "Biological and Medical Ontologies: Protein Ontology (PRO)". Encyclopedia of ... " - Protein Ontology". Archived from the original on 2011-03-10. Retrieved 2017-12-04. ... Biological databases, Genomics, Molecular biology, Proteins, Proteomics organizations). ... The Protein Ontology is another popular database released by the Protein Information Resource. ...
The Open Biological and Biomedical Ontologies (OBO; formerly Open Biomedical Ontologies) is an effort to create ontologies ( ... the CheBI ontology, the Disease Ontology, the Plant Ontology, the Sequence Ontology, the Ontology for Biomedical Investigations ... Most ontology developers in OBO use the Protégé ontology editor and the Web Ontology Language (OWL) for building ontologies. To ... The Open Biological and Biomedical Ontologies (OBO) Foundry is a group of people dedicated to build and maintain ontologies ...
... Consortium Gramene TAIR MaizeGDB NASC SoyBase v t e (Botany, Biological databases, All stub articles, Botany ... Plant ontology (PO) is a collection of ontologies developed by the Plant Ontology Consortium. These ontologies describe ... The Plant Ontology Consortium, C. (2002). "The Plant Ontology™ Consortium and Plant Ontologies". Comparative and Functional ... Ilic, Katica (2008). Albert, Burger (ed.). Plant Structure Ontology (PSO) - A morphological and anatomical ontology of ...
Biological ontologies are directed acyclic graphs of controlled vocabularies. They create categories for biological concepts ... Bioinformatics includes text mining of biological literature and the development of biological and gene ontologies to organize ... A gene ontology category, cellular component, has been devised to capture subcellular localization in many biological databases ... One of the most widespread is the Gene ontology which describes gene function. There are also ontologies which describe ...
I. Taxonomy of the producing organism, fermentation, HPLC analysis and biological activities". The Journal of Antibiotics. 46 ( ... "Finto: MeSH: Streptomyces antibioticus". finto: Finnish Thesaurus and Ontology Service. Retrieved 10 August 2015. Atta HM ( ... isolation and biological properties". Journal of Saudi Chemical Society. 19 (1): 12-22. doi:10.1016/j.jscs.2011.12.011. Oh DC, ...
See also: Jesús Mosterín (1994). "Mereology, Set Theory, and Biological Ontology". In D. Prawitz and D. Westerståhl (eds.): ... Mosterín has also tackled issues like the definition of life itself or the ontology of biological organisms and species. ... which combines the ontology of animals as paradigmatic individuals with the insights and results of biological research. This ... Concerning the ontological thesis of Michael Ghiselin and David Hull on the individuality of biological species, Mosterín shows ...
Illinois University Biological Computer Laboratory BCL Report 3.0. Urbana: Biological Computer Laboratory, University of ... In 1962, he published Cybernetic ontology and transjunctional operations. Later he lectured at the University of Hamburg until ... ISBN 3-7873-1033-9. 1962, Cybernetic Ontology and Transjunctional Operations. University of Illinois, Engineering Experiment ...
The Ontology for Biomedical Investigations (OBI) is an open-access, integrated ontology for the description of biological and ... Ontology for Biomedical Investigations (OBI) , Home "Basic Formal Ontology (BFO)". Institute for Formal Ontology and Medical ... The ontology has the scope of modeling all biomedical investigations and as such contains ontology terms for aspects such as: ... OBI uses the basic formal ontology upper-level ontology as a means of describing general entities that do not belong to a ...
Biological database Biological data visualization InterMine - an open-source biological data warehouse system Doms, A.; ... constructed a lattice work of three ontologies (for anatomy and development of model organisms) on a novel framework ontology ... For example, various 'omics' datasets may be integrated to provide biological insights into biological systems. Examples ... in this ontology would return the heart plans for each of the vertebrate species whose ontologies were included. The stated ...
He is also a co-organizer of the biological visualization conference Vizbi. Hunter cofounded and was a member of the Board of ... Livingston, Kevin M.; Bada, Michael; Baumgartner, William A.; Hunter, Lawrence E. (April 23, 2015). "KaBOB: ontology-based ... "VIZBI - Visualizing Biological Data". Retrieved April 12, 2018. ... in particular bio-ontologies, to the analysis of high-throughput data and of biomedical texts. He has proposed ...
Riboulet-Zemouli, Kenzi (2020). "'Cannabis' ontologies I: Conceptual issues with Cannabis and cannabinoids terminology". Drug ... Biological Psychiatry. 79 (7): 539-48. doi:10.1016/j.biopsych.2016.02.001. PMID 26970364. S2CID 36165555. Freeman MJ, Rose DZ, ... Riboulet-Zemouli, Kenzi (2020). "'Cannabis' ontologies I: Conceptual issues with Cannabis and cannabinoids terminology". Drug ... Biological Psychiatry. 39 (2): 234-243. doi:10.1016/j.pnpbp.2012.04.017. ISSN 1878-4216. PMC 3936256. PMID 22561602. ...
Gene Ontology Consortium. "AmiGO 2: Welcome". Gene Ontology, Consortium (January 2015). "Gene Ontology ... Multiple genes are linked to a single biological pathway, and so it is the additive change in expression within gene sets that ... Multi-Ontology Enrichment Tool (MOET): MOET is a web-based ontology analysis tool that provides functionality for multiple ... ontologies including GO and the human and mouse phenotype ontologies, signatures from cells treated with drugs, gene sets ...
2003). Using an Ontology to Evaluate a Large Rule Based Ontology: Theory and Practice. {\em Performance Metrics for Intelligent ... Knowledge Sharing across Biological and Medical Knowledge Based Systems, AAAI. Douglas Lenat and R. V. Guha (1990). Building ... Stephen Reed and D. Lenat (2002). "Mapping Ontologies into Cyc". In: AAAI 2002 Conference Workshop on Ontologies For The ... Expressivity and Efficiency in a Common-Sense Ontology". In: Papers from the AAAI Workshop on Contexts and Ontologies: Theory, ...
Dybkær, René (2004). "An ontology on property for physical, chemical, and biological systems". APMIS Suppl. (117): 1-210. PMID ...
Proceedings of the 9th International Conference on Biological Ontology: 2. Archived (PDF) from the original on 2019-01-14. ... Wimalanathan, Kokulapalan; Lawrence-Dill, Carolyn J. (18 October 2019). "Gene Ontology Meta Annotator for Plants". doi:10.1101/ ... Braun, Ian; Lawrence-Dill, Carolyn (2018). "Computational Classification of Phenologs Across Biological Diversity" (PDF). ... "An ontology approach to comparative phenomics in plants". Plant Methods. 11 (1): 10. doi:10.1186/s13007-015-0053-y. PMC 4359497 ...
"The database and ontology of Chemical Entities of Biological Interest". EMBL-EBI, European Molecular Biology Laboratory, ...
Chemical Entities of Biological Interest, also known as ChEBI, is a chemical database and ontology of molecular entities ... a database and ontology for chemical entities of biological interest". Nucleic Acids Research. 36 (Database issue): D344-50. ... "Chemical Entities of Biological Interest: an update". Nucleic Acids Research. 38 (Database issue): D249-54. doi:10.1093/nar/ ... Biological databases, Chemical databases, Chemical nomenclature, Science and technology in Cambridgeshire, South Cambridgeshire ...
Biological Species, Ontology, and the Metaphysics of Biology. Lanham, MD: Lexington Books. pp. 8. ISBN 0-7391-0503-5. Loux, ... ISBN 0-912516-35-6. Cocchiarella, Nino B. (2007). Formal Ontology and Conceptual Realism. Dordrecht: Springer Science & ... Peirce also held as a matter of ontology that what he called "thirdness", the more general facts about the world, are extra- ... he was a nominalist in his ontology: From every point of view, the overwhelming and portentous character ascribed to universal ...
"carbamoyl group (CHEBI:23004)". ChEBI: The database and ontology of Chemical Entities of Biological Interest. European ... Shaw WV, Tsai L, Stadtman ER (Feb 1966). "The enzymatic synthesis of N-methylglutamic acid". The Journal of Biological ... Identification of p35 as a novel regulatory subunit". The Journal of Biological Chemistry. 271 (1): 471-7. doi:10.1074/jbc. ... "EC 2.9.1". School of Biological & Chemical Sciences at Queen Mary, University of London. Nomenclature Committee of the ...
David N. Stamos (2003). The Species Problem: Biological Species, Ontology, and the Metaphysics of Biology. Lexington Books. p. ...
A database and ontology for chemical entities of biological interest". Nucleic Acids Research. 36 (Database issue): D344-D350. ... and is responsible for leading the team working on Chemical Entities of Biological Interest (ChEBI). He headed the ... "The ChEBI reference database and ontology for biologically relevant chemistry: Enhancements for 2013". Nucleic Acids Research. ...
Stamos, D.N. (2003). The species problem : biological species, ontology, and the metaphysics of biology. Lanham, Md. [u.a.]: ... In biological cladistics for the classification of organisms, monophyly is the condition of a taxonomic grouping being a clade ... A polyphyletic grouping meets neither criterion, and instead serves to characterize convergent relationships of biological ... Biological Journal of the Linnean Society. 94: 217-220. doi:10.1111/j.1095-8312.2008.00984.x. Ashlock, Peter D. (March 1971). " ...
Stamos, David N. (2003). The Species Problem: Biological Species, Ontology, and the Metaphysics of Biology. Lexington Books. p ... Unlike the biological species concept, a cladistic species does not rely on reproductive isolation - its criteria are ... Pimentel, David (2014). Biological Invasions: Economic and Environmental Costs of Alien Plant, Animal, and Microbe Species. CRC ... Most modern textbooks make use of Ernst Mayr's 1942 definition, known as the Biological Species Concept as a basis for further ...
The Gene Ontology Consortium is the set of biological databases and research groups actively involved in the gene ontology ... The Gene Ontology project provides an ontology of defined terms representing gene product properties. The ontology covers three ... "The Gene Ontology Resource". Gene Ontology Consortium. Sjcarbon,Gene Ontology Consortium Wiki (2013-07-10). "AmiGO_2_Manual: ... Deb, B. (2012). "An ontological analysis of some biological ontologies". Frontiers in Genetics. 3: 269. doi:10.3389/fgene. ...
Standards have been established to maintain and organize biological ontologies under the OBO (Open Biological Ontologies) ... Upper ontology: concepts supporting development of an ontology, meta-ontology. Domain ontology: concepts relevant to a ... Thing ontologies and fact ontologies are one-category-ontologies: they both hold that all fundamental entities belong to the ... p. 3. Look up ontology in Wiktionary, the free dictionary. Wikimedia Commons has media related to Ontology. "Ontology" . ...
Ontology-Based Integration and Preprocessing of Distributed Data. Biological and Medical Data Analysis. Springer Berlin ... The Protégé (software) is the standard tool for constructing an ontology.[citation needed] In general, the use of ontologies ... This application forms the ontology. From there, the ontology can be used to analyze data and process results. Fuzzy ... The idea is to build a dedicated ontology, which explains on a higher level what the problem is about. In regards to semantic ...
... only mean biological parent or mother and not social parent or mother. The W3C-endorsed OWL specification includes the ... OWL ontologies can import other ontologies, adding information from the imported ontology to the current ontology. An ontology ... Every legal OWL Lite ontology is a legal OWL DL ontology. Every legal OWL DL ontology is a legal OWL Full ontology. Every valid ... Consider an ontology for tea based on a Tea class. First, an ontology identifier is needed. Every OWL ontology must be ...
biological process involved in interspecies interaction between organisms + biological process involved in intraspecies ... biological phase + A distinct period or stage in a biological process or cycle. ... biological phase (GO:0044848). Annotations: Rat: (8) Mouse: (9) Human: (9) Chinchilla: (8) Bonobo: (8) Dog: (8) Squirrel: (8) ... Genes Projects (beta) QTLs Strains Markers Genome Information Ontologies Cell Lines References Download Submit Data ...
OBO-Edit, an ontology browser for most of the Open Biological and Biomedical Ontologies OBO Foundry, a suite of interoperable ... "Ontology browser for most of the Open Biological and Biomedical Ontologies". Berkeley Bioinformatics Open Source Project (BBOP ... Folksonomy Formal concept analysis Formal ontology Knowledge graph Lattice Ontology Ontology alignment Ontology chart Open ... The Gellish ontology is an example of a combination of an upper and a domain ontology. A survey of ontology visualization ...
... "in International Conference on Biomedical Ontology (ICBO 2018), 2018.*BibTex ...
Specifically, few Gene Ontology biological processes (BPs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were ... Enriched gene ontology biological processes (GO BPs). GO BP analysis after Gene set enrichment analysis (GSEA) allowed the ... Specifically, few Gene Ontology biological processes (BPs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were ... was performed on the fold-change ranked gene lists using the ClusterProfiler package with the Gene Ontology Biological Process ...
... "in International Conference on Biomedical Ontology (ICBO 2018), Corvallis, OR, 2008.*BibTex ...
Preconference Phenotype Ontology Workshop (August 6)-FREE. *Post Conference Machine Learning workshop organized by IBM and CGRB ... On the registration portal, you are allowed to combine registrations for the Phenotype Ontology, main ICBO, and/or the Machine ...
Accordingly, biological ontology mapping has attracted a lot of interest. In this paper, we introduce OBrowser, a semi- ... While being based on a classical ontology mapping architecture, OBrowser computes correspondences using a combination of ... Identifying correspondences between concepts of two ontologies (mapping) allows the reuse and sharing of annotations. ... Biological ontologies are widely used for genome annotation. ... Accordingly, biological ontology mapping has attracted a lot of ...
Submitted by justin on Tue, 08/02/2016 - 14:48 ...
Biological Ontologies* * Drug-Related Side Effects and Adverse Reactions / classification* * Drug-Related Side Effects and ... Ontologies to capture adverse events following immunisation (AEFI) from real world health data Stud Health Technol Inform. 2014 ... We describe a method using ontologies to be flag definite, probable or possible cases. We use Guillain-Barre syndrome (GBS) as ... Whilst there has been much research into the use of ontologies in immunisation these have focussed on database interrogation; ...
International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016). *Google Scholar ...
Semantic Webs and Ontology-driven Biological Data Integration Methods for Bacteria Authors. * M. U. G. Khan Department of ... M. U. G. Khan, M. Idrees, U. Hayat, and A. Akram, "Semantic Webs and Ontology-driven Biological Data Integration Methods for ... M. Idrees, M. U. G. Khan, SMGCD: METRICS FOR BIOLOGICAL SEQUENCE DATA , The Nucleus: Vol. 51 No. 1 (2014) ... M.A. Remli, S. Deris and A. Abdullah, Ontology-based Semantic Data Integration for Lactococcus Lactis (L.lactis): Connecting ...
... and a meta-analysis of 17 experiments with up to 18 biological conditions, eight biological replicates and 100 million (M) ... For the practitioners of the tomato community, on the basis of the meta-analysis, we recommend at least 4 biological replicates ... with eight biological replicates per condition) to compare the results with previous benchmark studies, ... and a meta-analysis from 17 experiments with up to 18 biological conditions, 8 replicates and 100 million reads per sample. As ...
The Ontology of Biological and Clinical Statistics (OBCS) is a biomedical ontology in the domain of biological and clinical ... Ontology of Biological and Clinical Statistics A biomedical ontology in the domain of biological and clinical statistics. ... OBCS is primarily targeted for statistical term representation in the fields in biological, biomedical, and clinical domains. ...
Discovering microbe functionality in human disease with a gene-ontology-aware model. Proc. Biological Ontologies and Knowledge ... Microbial Gene Ontology informed deep neural network for microbe functionality discovery in human diseases. PLoS One, 2023 Aug ... Hirose O, Yoshida R, Yamaguchi R, Imoto S, Higuchi T, Miyano S. Analyzing time course gene expression data with biological and ... Niida A, Tremmel G, Imoto S, Miyano S. Multilayer cluster heat map visualizing biological tensor data. Lecture Notes in ...
9:00-noon: Introduction to the Protein Ontology Flow Cytometry Driving Biological Project ... The Gene Ontology, Reactome, The Immunology Ontology, The Immune Epitope Ontology and the Allergy Ontology. ... Updates on the Vital Sign Ontology. Recipes for OGMS-conformant extension ontologies. Close: 6:00pm. Relevant ontology efforts ... Vaccine Ontology (Oliver He). AO Allergy Ontology (Alex C. Yu). ND Neurological Disease Ontology (Alexander Diehl). ...
regulation of biological process. 12912. regulation of metabolic process. 7335. negative regulation of metabolic process. 3628 ... Genes Community Projects (beta) QTLs Strains Markers Genome Information Ontologies Cell Lines References Download Submit Data ... OntoMate (Literature Search) JBrowse (Genome Browser) Synteny Browser (VCMap) (beta) Variant Visualizer Multi-Ontology ...
Accelerating Behavioral and Social Science through Ontology Development and Use: Research Network Projects (U01 Clinical Trial ... Unified Medical Language System knowledge sources or ontologies found on the Open Biological and Biomedical Ontologies Foundry ... Unified Medical Language System knowledge sources or ontologies found on the Open Biological and Biomedical Ontologies Foundry ... Unified Medical Language System knowledge sources or ontologies found on the Open Biological and Biomedical Ontologies Foundry ...
1.1 The DEB Ontology. The Devices, Experimental scaffolds and Biomaterials Ontology (DEB) is an open resource for organizing ... 2. An article detailing the development of the DEB ontology:. O. Hakimi; J.L. Gelpi; M. Krallinger; F. Curi; D. Repchevsky; M.P ... Like all of DEBBIEs generated assets, DEB is open source, and can be downloaded from: ... Periodic Reporting for period 1 - DEBBIE (A database of experimental biomaterials and their biological effect). Reporting ...
Open Biological and Biomedical Ontologies (OBO). Open-i Project - An Open Access Biomedical Image ... Biological Informatics 2020 is a comprehensive listing of biological informatics resources currently available on the Internet ... Biological Informatics 2020. By Marcus P. Zillman, 26 May 2020 "Bioinformatics is an interdisciplinary field that develops ... BIOLOGICAL INFORMATICS. HEALTH INFORMATICS (Medical Informatics). NEUROINFORMATICS (NI). BIODIVERSITY INFORMATICS (BDI). ...
Gene ontology (GO) and pathway analyses. (a) GO biological process analysis of the targets. Y-axis: top 15 biological processes ... Gene Ontology and Pathway Analysis. Target enrichment gene ontology (GO) and pathway analyses lead us to gain mechanistic ... gene ontology. First, 51 active compounds of formula were selected from the TCMSP database. Their biological targets were ... The top 15 biological process GO terms with False Discovery Rate (FDR) , 0.01 are ranked by enrichment score (-logFDR) in ...
Biological profiling of gene groups utilizing Gene Ontology. Genome Inform 16, 106-115 (2005) ... Gene Ontology terms were assigned using Blast2GO31 software (BLASTP 1 × 1020) and tested for enrichment using Fishers exact ... College of Biological Sciences Imaging Center for spore micrographs. ...
First, gene expression data was annotated by some broad Gene Ontology (GO) terms, according to their positions in Directed ... It is necessary to generate hypotheses about functions or biological processes for unknown genes to help design more meaningful ... Finding out or estimating what functions or biological processes a gene involves can help interpret and understand the ... or genes with similar functions or biological processes share the similar expression profiles. In fact, genes with different ...
... provides comprehensive integrated biological information for the budding yeast Saccharomyces cerevisiae. ... Gene Ontology Gene Ontology (GO) terms that describe the function of a complex, the biological process in which it participates ... Biological Process. *involved in cellular respiration (IDA). *involved in mitochondrial electron transport, ubiquinol to ... This diagram displays Gene Ontology terms (green) and subunits (blue) that are shared between the given macromolecular complex ...
... provides comprehensive integrated biological information for the budding yeast Saccharomyces cerevisiae. ... Gene Ontology Gene Ontology (GO) terms that describe the function of a complex, the biological process in which it participates ... Biological Process. *involved in autophagosome assembly (BSR). *acts upstream of or within positive regulation of protein ... This diagram displays Gene Ontology terms (green) and subunits (blue) that are shared between the given macromolecular complex ...
... provides comprehensive integrated biological information for the budding yeast Saccharomyces cerevisiae. ... Gene Ontology Gene Ontology (GO) terms that describe the function of a complex, the biological process in which it participates ... This diagram displays Gene Ontology terms (green) and subunits (blue) that are shared between the given macromolecular complex ...
OBO Open Biological Ontologies Prot g Ontologies Library, Stanford Medical Informatics, Stanford ... An ontology consists of a set of concepts, axioms, and relationships that describe a domain of interest. An upper ontology is ... In the context of knowledge sharing, I use the term ontology to mean a specification of a conceptualization Ontologies are ... See Ontology Spectrum for variations in meanings of ontology ...
Hoehndorf, R., Loebe, F., Poli, R., Herre, H., & Kelso, J. (2008). GFO-Bio: A biological core ontology. Applied ontology, 3(4 ... Hoehndorf, R., Kelso, J., & Herre, H. (2009). The ontology of biological sequences. BMC Bioinformatics, 10: 377. Open Access ... A top-level ontology of functions and its application in the Open Biomedical Ontologies. Bioinformatics, 22(14), e66-e73. Open ... a community-defined information specification for biological databases. Database: the Journal of Biological Databases and ...
Any process that modulates the frequency, rate or extent of a biological process. Biological processes are regulated by many ... Ontology explorer. Gene ontology Change ontology:. anatomy. Arabidopsis gross anatomy. BTO (BRENDA Tissue Ontology). CAVEman: ...
Semantic Web and Ontology Semi-Structural Data Management, Meta Data, and XML Spatial and Temporal Databases Statistical and ... Scientific, Biological and Bioinformatics Data Management and Data Mining Semantic Modeling and Management of Web-Based ...
Selected articles from the Biological Ontologies and Knowledge bases workshop 2019. The full contents of the supplement are ... In recent years, high-throughput biological techniques and large-scale experimental approaches for PPIs identification have ... biological techniques and large-scale experiments are often expensive, time-consuming and labor-intensive [6, 7]. Calculation- ... based methods can solve the problem to a certain extent, and provide reference and guidance for the biological experiment ...
  • The National Center for Biomedical Ontology (NCBO) in collaboration with the Protein Ontology (PRO) and the Infectious Disease Ontology (IDO) will host a three-day dissemination workshop in Buffalo, NY on June 11-13, 2012. (
  • As a Semantic Web application domain, Gene Ontology Consortium provides a RDF-XML data file . (
  • Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data, in particular when the data sets are large and complex. (
  • As an interdisciplinary field of science, bioinformatics combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret the biological data. (
  • The Protein Structure and Bioinformatics (LU PSB) develops methods and performs analyses to understand biological and medical phenomena at genetic, functional, mechanical and systems level. (
  • Bioinformatics, the application of computational methods to biological and biomedical problems, is a rapidly growing field. (
  • On the registration portal, you are allowed to combine registrations for the Phenotype Ontology, main ICBO, and/or the Machine Learning workshop. (
  • Curation and expansion of the Human Phenotype Ontology for systemic autoinflammatory diseases improves phenotype-driven disease-matching. (
  • Accurate and standardized phenotypic descriptions are essential in diagnosing rare diseases and discovering new diseases , and the Human Phenotype Ontology (HPO) system was developed to provide a rich collection of hierarchical phenotypic descriptions. (
  • M. Lange , " ICBO_2018_76: Designing and Building the IC-FOODS Foundry: Community, Technology, and Standards for a Semantic Web of Food " , in International Conference on Biomedical Ontology (ICBO 2018) , Corvallis, OR, 2008. (
  • It has been developed by the Web Ontology Working Group as part of the W3C Semantic Web Activity ( Activity Statement , Group Charter ) for publication on 15 December 2003. (
  • The growing need for integration of diverse and heterogeneous data sets from distinct communities of scientists in separate biological research fields has thus been the major driving force to migrate from traditional XML to Semantic Web [ 2 ]. (
  • Projects should address health-related behavioral and social science problems not easily solved without improvement in semantic knowledge structures (e.g., controlled vocabularies, taxonomies, and ontologies). (
  • Identifying correspondences between concepts of two ontologies (mapping) allows the reuse and sharing of annotations. (
  • In Reactome we have integrated annotations of human TLR molecular functions with those of 6800 other human proteins involved in diverse biological processes to generate a resource suitable for data mining, pathway analysis, and other systems biology approaches. (
  • The most renowned biological ontology, Gene Ontology (GO) is widely used for annotations of genes and gene products of different organisms. (
  • Specifically, few Gene Ontology biological processes (BPs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were modulated after a short (24H) compared to a long (48H) treatment. (
  • The Gene Ontology contains a wealth of terms covering immune system processes for the annotation of proteins involved in the functioning of the immune system. (
  • The results of these analyses revealed that the differentially expressed exosomal miRNAs participate in multiple biological processes, such as gene expression, synthesis of biomolecules, cell development, differentiation, and signal transduction, among others. (
  • Finding out or estimating what functions or biological processes a gene involves can help interpret and understand the biological metabolic pathways. (
  • It is necessary to generate hypotheses about functions or biological processes for unknown genes to help design more meaningful experiments. (
  • The traditional methods of microarray data analysis are based on the assumption that genes with similar expression profiles share the similar functions or biological processes, or genes with similar functions or biological processes share the similar expression profiles. (
  • Biological ontologies are widely used for genome annotation. (
  • The Biomaterials Annotator is the first biomaterials-specific annotation system, designed to recognize named entities from fifteen different categories, pre-defined in the DEB ontology. (
  • Unlike the commonly used clustering methods, which start the analysis directly with the expression profiles, we used both the background knowledge (Gene Ontology annotation) and expression profiles during the analysis. (
  • U. Consortium, The Gene Ontology (GO) Project in 2006. (
  • However, there are shortcomings in the Resource Description Framework (RDF) data file provided by the GO consortium: 1) Lack of sufficient semantic relationships between pairs of terms coming from the three independent GO sub-ontologies, that limit the power to provide complex semantic queries and inference services based on it. (
  • International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016). (
  • We also analyzed the impact of both the replicate number and library size on gene ontology (GO) enrichment analysis. (
  • It has become a prevalent technology, allowing an efficient genome-wide relative quantification of gene expression and, in particular, it is the method of choice to find differentially expressed genes between two or more biological conditions of interest. (
  • Liu Y, Zhang YZ, Imoto S . Microbial Gene Ontology informed deep neural network for microbe functionality discovery in human diseases. (
  • First, gene expression data was annotated by some broad Gene Ontology (GO) terms, according to their positions in Directed Acyclic Graph (DAG) of GO. (
  • Gene Ontology (GO) terms that describe the function of a complex, the biological process in which it participates, or its cellular location. (
  • This diagram displays Gene Ontology terms (green) and subunits (blue) that are shared between the given macromolecular complex (black) and other yeast complexes (yellow). (
  • Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on differentially expressed genes (DEGs). (
  • Gene Ontology and network analysis confirmed that IL-5 was a key cytokine in many of the upregulated immune networks. (
  • We will outline use of the ontology for immune assay integration and statistical enrichment analysis. (
  • Quine and Kripke in philosophy, Sowa and Guarino in information science), and debates concerning to what extent normative ontology is possible (e.g., foundationalism and coherentism in philosophy, BFO and Cyc in artificial intelligence). (
  • AI researchers argued that they could create new ontologies as computational models that enable certain kinds of automated reasoning, which was only marginally successful. (
  • The research projects must include multi-disciplinary teams of subject matter experts in one or more BSSR fields, as well as ontology related informatics and computational approaches. (
  • The biological system is complex with many regulatory features such as DNA, mRNA, proteins, metabolites, and epigenetic features such as DNA methylation and histone post-translational modifications (PTMs). (
  • Upstream transcription factor 1 (USF1) is a canonical transcription factor (TF) and is associated with the pathogenesis of several cancers, but its biological functions and molecular targets in HCC remain unclear. (
  • A structured classification of molecular entities of biological interest focusing on 'small' chemical compounds. (
  • GO has three independent subontologies, Cellular Component, Biological Process and Molecular Function. (
  • Day 2 will be focused on flow cytometry, including the question of the Cell and Protein Ontologies and of the role of surface protein expression in cell type classification. (
  • The OWL Web Ontology Language is intended to provide a language that can be used to describe the classes and relations between them that are inherent in Web documents and applications. (
  • We describe a method using ontologies to be flag definite, probable or possible cases. (
  • An ontology consists of a set of concepts, axioms, and relationships that describe a domain of interest. (
  • Will describe initial work on an ontology of cellular immune networks that is designed to capture the qualitative cytokine expression patterns and cellular phenotypes associated with specific immune activation networks (e.g. (
  • Every academic discipline or field creates ontologies to limit complexity and organize data into information and knowledge. (
  • Improved ontologies may improve problem solving within that domain, interoperability of data systems, and discoverability of data. (
  • Another important issue was the need for normalization of the data to correctly compare two different biological conditions by assessing and erasing all eventual technical and/or biological biases. (
  • Day 3 will include a session devoted to the use of ontologies to assist clinicians working with infectious disease data, followed by a session on the Ontology for General Medical Science. (
  • This new situation demands appropriate IT-infrastructures, where biological and medical data can be processed within an acceptable timespan - reaching from minutes in health-care applications to days in large-scale research projects. (
  • In recent years, high-throughput biological techniques and large-scale experimental approaches for PPIs identification have achieved tremendous development, lots of PPIs data from different organisms has been discovered by researchers [ 2 ]. (
  • Data management is a key step in present biological projects. (
  • As part of the Spanish node of the ELIXIR European infrastructure is collaborating in the definition of the guidelines, and to generate tools to ease biological data management. (
  • We propose a RDF model, GORouter , which encodes heterogeneous original data in a uniform RDF format, creates additional ontology mappings between GO terms, and introduces a set of inference rulebases. (
  • and (3) approaches to ally, understanding ADME leads to a more complete use of integrating PBPK model outputs with other HHRA tools, including biological and toxicological data to support route-to-route and benchmark dose modeling. (
  • In the 1980s, the AI community began to use the term ontology to refer to both a theory of a modeled world and a component of knowledge-based systems. (
  • Ontology is a term borrowed from philosophy that refers to the science of describing the kinds of entities in the world and how they are related. (
  • OBCS is primarily targeted for statistical term representation in the fields in biological, biomedical, and clinical domains. (
  • In the context of knowledge sharing, I use the term ontology to mean a specification of a conceptualization Ontologies are often equated with taxonomic hierarchies of classes, but class definitions, and the subsumption relation, but ontologies need not be limited to these forms. (
  • An upper ontology is limited to concepts that are meta, generic, abstract and philosophical, and therefore are general enough to address (at a high level) a broad range of domain areas. (
  • The word 'ontology' seems to generate a lot of controversy in discussions about AI [artificial intelligence]. (
  • The system interlinks three ontologies, comprising anatomical, developmental and taxonomical information, and includes instances of structures for different species. (
  • For individuals working on tomato research, on the basis of the meta-analysis, we recommend at least four biological replicates per condition and 20 M reads per sample to be almost sure of obtaining about 1000 DE genes if they exist. (
  • Day 1 will provide a survey of current ontology-based research in immunology and infectious disease with a view to future coordination among ontology developers and users in this field. (
  • This Notice of Funding Opportunity (NOFO) invites applications to support research projects focused on the expansion of existing or development of new ontologies for behavioral or social science research (BSSR). (
  • PAR-23-181 ) and the other funded projects in a Behavioral and Social Science Ontology Development U01 Research Network. (
  • The other research line in highly related and investigates the effects of the variations and perturbations as systems biological and medical level. (
  • Research interest: I am interested in the philosophy of action, broadly conceived, as well as the philosophy of psychology/cognitive science and social ontology. (
  • Calculation-based methods can solve the problem to a certain extent, and provide reference and guidance for the biological experiment design, which are helpful for laboratory validation. (
  • Artificial intelligence has retained considerable attention regarding applied ontology in subfields like natural language processing within machine translation and knowledge representation, but ontology editors are being used often in a range of fields, including biomedical informatics, industry. (
  • We will introduce the Liver Immunology Ontology (LIO), which has as primary goal the representation of the immune response induced in the context of the liver. (
  • Any process that modulates the frequency, rate or extent of a biological process. (
  • More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of terms and relational expressions that represent the entities in that subject area. (
  • BASE users are free to annotate biomaterials (and most BASE items) as they wish, from basic free text description to more advanced ontology based terms. (
  • Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. (
  • A distinct period or stage in a biological process or cycle. (
  • An emerging scenario is uncovering immune response as a sophisticated biological process, which requires an intensive cross-talk between immunocytes, parenchymal and stromal cell types. (
  • Tools or resources must also account for socio-behavioral cultural context in vocabulary/ontology development. (
  • A biomedical ontology in the domain of biological and clinical statistics. (
  • Ontology is a branch of philosophy and intersects areas such as metaphysics, epistemology, and philosophy of language, as it considers how knowledge, language, and perception relate to the nature of reality. (
  • In present paper, we presented an ontology based effort for the development of a knowledge that would allow for semantically querying bacteria knowledge base. (
  • Biological systems are often very complex so that an appropriate formalism is needed for modeling their behavior. (
  • What ontologies in both information science and philosophy have in common is the attempt to represent entities, including both objects and events, with all their interdependent properties and relations, according to a system of categories. (
  • To cover entities from the different domains, multiple nomenclature, vocabularies, and ontologies were identified and combined. (
  • However, a common assumption in the philosophy of joint action and social ontology is that a clear distinction can be drawn between joint actions and mere sets of interdependent actions. (
  • An OWL ontology may include descriptions of classes , properties and their instances. (
  • We present a novel approach to modelling biological information using ontologies. (
  • For instance, the definition and ontology of economics is a primary concern in Marxist economics, but also in other subfields of economics. (
  • While the main drawback of previous relevant studies is the lack of generality, we conducted both an analysis of a two-condition experiment (with eight biological replicates per condition) to compare the results with previous benchmark studies, and a meta-analysis of 17 experiments with up to 18 biological conditions, eight biological replicates and 100 million (M) reads per sample. (
  • In both fields, there is considerable work on problems of ontology engineering (e.g. (
  • Applied ontology is considered by some as a successor to prior work in philosophy. (