Dictionaries, MedicalDictionaries as Topic: Lists of words, usually in alphabetical order, giving information about form, pronunciation, etymology, grammar, and meaning.Dictionaries, ChemicalDictionaryDictionaries, PharmaceuticTerminology as Topic: The terms, expressions, designations, or symbols used in a particular science, discipline, or specialized subject area.Dictionaries, DentalDictionaries, PolyglotDictionaries, ClassicalAbbreviations as Topic: Shortened forms of written words or phrases used for brevity.Natural Language Processing: Computer processing of a language with rules that reflect and describe current usage rather than prescribed usage.Abstracting and Indexing as Topic: Activities performed to identify concepts and aspects of published information and research reports.Unified Medical Language System: 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.Names: Personal names, given or surname, as cultural characteristics, as ethnological or religious patterns, as indications of the geographic distribution of families and inbreeding, etc. Analysis of isonymy, the quality of having the same or similar names, is useful in the study of population genetics. NAMES is used also for the history of names or name changes of corporate bodies, such as medical societies, universities, hospitals, government agencies, etc.Information Storage and Retrieval: Organized activities related to the storage, location, search, and retrieval of information.Encyclopedias as Topic: Works containing information articles on subjects in every field of knowledge, usually arranged in alphabetical order, or a similar work limited to a special field or subject. (From The ALA Glossary of Library and Information Science, 1983)Artificial Intelligence: 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.Subject Headings: Terms or expressions which provide the major means of access by subject to the bibliographic unit.Algorithms: A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.MEDLINE: The premier bibliographic database of the NATIONAL LIBRARY OF MEDICINE. MEDLINE® (MEDLARS Online) is the primary subset of PUBMED and can be searched on NLM's Web site in PubMed or the NLM Gateway. MEDLINE references are indexed with MEDICAL SUBJECT HEADINGS (MeSH).Pattern Recognition, Automated: In INFORMATION RETRIEVAL, machine-sensing or identification of visible patterns (shapes, forms, and configurations). (Harrod's Librarians' Glossary, 7th ed)Data Mining: Use of sophisticated analysis tools to sort through, organize, examine, and combine large sets of information.Software: Sequential operating programs and data which instruct the functioning of a digital computer.Programming Languages: Specific languages used to prepare computer programs.Semantics: The relationships between symbols and their meanings.Database Management Systems: Software designed to store, manipulate, manage, and control data for specific uses.Automatic Data Processing: Data processing largely performed by automatic means.Physics: The study of those aspects of energy and matter in terms of elementary principles and laws. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 6th ed)Systems Integration: 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)Databases as Topic: Organized collections of computer records, standardized in format and content, that are stored in any of a variety of computer-readable modes. They are the basic sets of data from which computer-readable files are created. (from ALA Glossary of Library and Information Science, 1983)Data Compression: Information application based on a variety of coding methods to minimize the amount of data to be stored, retrieved, or transmitted. Data compression can be applied to various forms of data, such as images and signals. It is used to reduce costs and increase efficiency in the maintenance of large volumes of data.Computational Biology: 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.Periodicals as Topic: A publication issued at stated, more or less regular, intervals.RxNorm: A standardized nomenclature for clinical drugs and drug delivery devices. It links its names to many of the drug vocabularies commonly used in pharmacy management.Multilingualism: The ability to speak, read, or write several languages or many languages with some facility. Bilingualism is the most common form. (From Random House Unabridged Dictionary, 2d ed)PubMed: 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.Databases, Protein: Databases containing information about PROTEINS such as AMINO ACID SEQUENCE; PROTEIN CONFORMATION; and other properties.Databases, Factual: 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.Systematized Nomenclature of Medicine: Controlled vocabulary of clinical terms produced by the International Health Terminology Standards Development Organisation (IHTSDO).Medical Records Systems, Computerized: Computer-based systems for input, storage, display, retrieval, and printing of information contained in a patient's medical record.Internet: 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.Databases, Bibliographic: Extensive collections, reputedly complete, of references and citations to books, articles, publications, etc., generally on a single subject or specialized subject area. Databases can operate through automated files, libraries, or computer disks. The concept should be differentiated from DATABASES, FACTUAL which is used for collections of data and facts apart from bibliographic references to them.Translating: Conversion from one language to another language.User-Computer Interface: The portion of an interactive computer program that issues messages to and receives commands from a user.Proteins: 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.Medical Informatics: The field of information science concerned with the analysis and dissemination of medical data through the application of computers to various aspects of health care and medicine.Online Systems: Systems where the input data enter the computer directly from the point of origin (usually a terminal or workstation) and/or in which output data are transmitted directly to that terminal point of origin. (Sippl, Computer Dictionary, 4th ed)Disease: A definite pathologic process with a characteristic set of signs and symptoms. It may affect the whole body or any of its parts, and its etiology, pathology, and prognosis may be known or unknown.Hospital Information Systems: Integrated, computer-assisted systems designed to store, manipulate, and retrieve information concerned with the administrative and clinical aspects of providing medical services within the hospital.Documentation: 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.Models, Statistical: Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.Shewanella: A genus of gram-negative, facultatively anaerobic rods. It is a saprophytic, marine organism which is often isolated from spoiling fish.Adverse Drug Reaction Reporting Systems: Systems developed for collecting reports from government agencies, manufacturers, hospitals, physicians, and other sources on adverse drug reactions.Pharmaceutical Preparations: Drugs intended for human or veterinary use, presented in their finished dosage form. Included here are materials used in the preparation and/or formulation of the finished dosage form.Software Design: Specifications and instructions applied to the software.Databases, Genetic: Databases devoted to knowledge about specific genes and gene products.

The CATH Dictionary of Homologous Superfamilies (DHS): a consensus approach for identifying distant structural homologues. (1/73)

A consensus approach has been developed for identifying distant structural homologues. This is based on the CATH Dictionary of Homologous Superfamilies (DHS), a database of validated multiple structural alignments annotated with consensus functional information for evolutionary protein superfamilies (URL: http://www. biochem.ucl.ac.uk/bsm/dhs). Multiple structural alignments have been generated for 362 well-populated superfamilies in the CATH structural domain database and annotated with secondary structure, physicochemical properties, functional sequence patterns and protein-ligand interaction data. Consensus functional information for each superfamily includes descriptions and keywords extracted from SWISS-PROT and the ENZYME database. The Dictionary provides a powerful resource to validate, examine and visualize key structural and functional features of each homologous superfamily. The value of the DHS, for assessing functional variability and identifying distant evolutionary relationships, is illustrated using the pyridoxal-5'-phosphate (PLP) binding aspartate aminotransferase superfamily. The DHS also provides a tool for examining sequence-structure relationships for proteins within each fold group.  (+info)

Organizing the present, looking to the future: an online knowledge repository to facilitate collaboration. (2/73)

BACKGROUND: Comprehensive data available in the Canadian province of Manitoba since 1970 have aided study of the interaction between population health, health care utilization, and structural features of the health care system. Given a complex linked database and many ongoing projects, better organization of available epidemiological, institutional, and technical information was needed. OBJECTIVE: The Manitoba Centre for Health Policy and Evaluation wished to develop a knowledge repository to handle data, document research Methods, and facilitate both internal communication and collaboration with other sites. METHODS: This evolving knowledge repository consists of both public and internal (restricted access) pages on the World Wide Web (WWW). Information can be accessed using an indexed logical format or queried to allow entry at user-defined points. The main topics are: Concept Dictionary, Research Definitions, Meta-Index, and Glossary. The Concept Dictionary operationalizes concepts used in health research using administrative data, outlining the creation of complex variables. Research Definitions specify the codes for common surgical procedures, tests, and diagnoses. The Meta-Index organizes concepts and definitions according to the Medical Sub-Heading (MeSH) system developed by the National Library of Medicine. The Glossary facilitates navigation through the research terms and abbreviations in the knowledge repository. An Education Resources heading presents a web-based graduate course using substantial amounts of material in the Concept Dictionary, a lecture in the Epidemiology Supercourse, and material for Manitoba's Regional Health Authorities. Confidential information (including Data Dictionaries) is available on the Centre's internal website. RESULTS: Use of the public pages has increased dramatically since January 1998, with almost 6,000 page hits from 250 different hosts in May 1999. More recently, the number of page hits has averaged around 4,000 per month, while the number of unique hosts has climbed to around 400. CONCLUSIONS: This knowledge repository promotes standardization and increases efficiency by placing concepts and associated programming in the Centre's collective memory. Collaboration and project management are facilitated.  (+info)

The role of definitions in biomedical concept representation. (3/73)

The Foundational Model (FM) of anatomy, developed as an anatomical enhancement of UMLS, classifies anatomical entities in a structural context. Explicit definitions have played a critical role in the establishment of FM classes. Essential structural properties that distinguish a group of anatomical entities serve as the differentiate for defining classes. These, as well as other structural attributes, are introduced as template slots in Protege, a frame-based knowledge acquisition system, and are inherited by descendants of the class. A set of desiderata has evolved during the instantiation of the FM for formulating definitions. We contend that 1. these desiderata generalize to non-anatomical domains and 2. satisfying them in constituent vocabularies of UMLS would enhance the quality of information retrievable through UMLS.  (+info)

Creating an online dictionary of abbreviations from MEDLINE. (4/73)

OBJECTIVE: The growth of the biomedical literature presents special challenges for both human readers and automatic algorithms. One such challenge derives from the common and uncontrolled use of abbreviations in the literature. Each additional abbreviation increases the effective size of the vocabulary for a field. Therefore, to create an automatically generated and maintained lexicon of abbreviations, we have developed an algorithm to match abbreviations in text with their expansions. DESIGN: Our method uses a statistical learning algorithm, logistic regression, to score abbreviation expansions based on their resemblance to a training set of human-annotated abbreviations. We applied it to Medstract, a corpus of MEDLINE abstracts in which abbreviations and their expansions have been manually annotated. We then ran the algorithm on all abstracts in MEDLINE, creating a dictionary of biomedical abbreviations. To test the coverage of the database, we used an independently created list of abbreviations from the China Medical Tribune. MEASUREMENTS: We measured the recall and precision of the algorithm in identifying abbreviations from the Medstract corpus. We also measured the recall when searching for abbreviations from the China Medical Tribune against the database. RESULTS: On the Medstract corpus, our algorithm achieves up to 83% recall at 80% precision. Applying the algorithm to all of MEDLINE yielded a database of 781,632 high-scoring abbreviations. Of all the abbreviations in the list from the China Medical Tribune, 88% were in the database. CONCLUSION: We have developed an algorithm to identify abbreviations from text. We are making this available as a public abbreviation server at \url[http://abbreviation.stanford.edu/].  (+info)

Finding relevant references to genes and proteins in Medline using a Bayesian approach. (5/73)

MOTIVATION: Mining the biomedical literature for references to genes and proteins always involves a tradeoff between high precision with false negatives, and high recall with false positives. Having a reliable method for assessing the relevance of literature mining results is crucial to finding ways to balance precision and recall, and for subsequently building automated systems to analyze these results. We hypothesize that abstracts and titles that discuss the same gene or protein use similar words. To validate this hypothesis, we built a dictionary- and rule-based system to mine Medline for references to genes and proteins, and used a Bayesian metric for scoring the relevance of each reference assignment. RESULTS: We analyzed the entire set of Medline records from 1966 to late 2001, and scored each gene and protein reference using a Bayesian estimated probability (EP) based on word frequency in a training set of 137837 known assignments from 30594 articles to 36197 gene and protein symbols. Two test sets of 148 and 150 randomly chosen assignments, respectively, were hand-validated and categorized as either good or bad. The distributions of EP values, when plotted on a log-scale histogram, are shown to markedly differ between good and bad assignments. Using EP values, recall was 100% at 61% precision (EP=2 x 10(-5)), 63% at 88% precision (EP=0.008), and 10% at 100% precision (EP=0.1). These results show that Medline entries discussing the same gene or protein have similar word usage, and that our method of assessing this similarity using EP values is valid, and enables an EP cutoff value to be determined that accurately and reproducibly balances precision and recall, allowing automated analysis of literature mining results. .  (+info)

The Protein Data Bank and structural genomics. (6/73)

The Protein Data Bank (PDB; http://www.pdb.org/) continues to be actively involved in various aspects of the informatics of structural genomics projects--developing and maintaining the Target Registration Database (TargetDB), organizing data dictionaries that will define the specification for the exchange and deposition of data with the structural genomics centers and creating software tools to capture data from standard structure determination applications.  (+info)

Social capital. (7/73)

This glossary aims to provide readers with some of the key terms that are relevant to a consideration of the relevance of social capital for health, and to introduce some of the debates on the concepts.  (+info)

Extraction of protein interaction information from unstructured text using a context-free grammar. (8/73)

MOTIVATION: As research into disease pathology and cellular function continues to generate vast amounts of data pertaining to protein, gene and small molecule (PGSM) interactions, there exists a critical need to capture these results in structured formats allowing for computational analysis. Although many efforts have been made to create databases that store this information in computer readable form, populating these sources largely requires a manual process of interpreting and extracting interaction relationships from the biological research literature. Being able to efficiently and accurately automate the extraction of interactions from unstructured text, would greatly improve the content of these databases and provide a method for managing the continued growth of new literature being published. RESULTS: In this paper, we describe a system for extracting PGSM interactions from unstructured text. By utilizing a lexical analyzer and context free grammar (CFG), we demonstrate that efficient parsers can be constructed for extracting these relationships from natural language with high rates of recall and precision. Our results show that this technique achieved a recall rate of 83.5% and a precision rate of 93.1% for recognizing PGSM names and a recall rate of 63.9% and a precision rate of 70.2% for extracting interactions between these entities. In contrast to other published techniques, the use of a CFG significantly reduces the complexities of natural language processing by focusing on domain specific structure as opposed to analyzing the semantics of a given language. Additionally, our approach provides a level of abstraction for adding new rules for extracting other types of biological relationships beyond PGSM relationships. AVAILABILITY: The program and corpus are available by request from the authors.  (+info)

  • This is regrettable, firstly, given the pedagogical value of dictionaries, which McArthur ( 1986 , 1998 ) regards as containers of knowledge and, secondly, given the amount of resources that are expended on dictionary making in terms of money, labour and time. (springer.com)
  • Actually, there are a number of books that include information on dog barks as communication, but most of them have quite extended discussions of barking, rather than providing a quick lookup definition, like a dictionary might. (psychologytoday.com)
  • www.dictionary.com/browse/isotope Isotope definition, any of two or more forms of a chemical element, having the same number of protons in the nucleus, or the same atomic number, but having different numbers of neutrons in the nucleus, or different atomic weights. (lycos.com)
  • www.merriam-webster.com/dictionary/isotope Isotope definition is - any of two or more species of atoms of a chemical element with the same atomic number and nearly identical chemical behavior but with differing atomic mass or mass number and different physical properties. (lycos.com)
  • Use this tool to search for dictionary entries in all lexica. (tufts.edu)
  • Both geographic names and biographical entries are selectively included in some dictionaries but are really encyclopaedic. (britannica.com)
  • The dictionary will include over 40,000 entries such as terminologies, ancient books and records, historic figures and scenic spots related to Tibetan Buddhism, according to the Northwest University for Nationalities, based in Lanzhou, capital of Gansu Province. (chinadaily.com.cn)
  • Along with its handy size, a cross-referencing system helps make the Dictionary as user friendly as possible and draws the content together, while the many tips, tables, line drawings and photographs (including a colour section) expand on entries and summarize information on essential points. (elsevier.com)
  • I wonder if there is a possibility to order the list of dictionary databases? (murga-linux.com)
  • Like this the list of available dictionaries is not updated at every start. (murga-linux.com)
  • Your instructions are close, though not fully correct (with Puppy 3.01's built-in PBdict, the dictionary list written to PB-dict.txt is overwritten further down in main.pb). (murga-linux.com)
  • The examples focus on the differences between lists and dictionaries, and on those cases where the use of a dictionary is a better alternative to the list-based solutions developed in Part 3 on built-in lists. (ibm.com)
  • You create a dictionary in Vimscript by using curly braces around a list of key/value pairs. (ibm.com)
  • One day the author was making his way through a ctf challenge, and he thought about how powerful a single dictionary could become if only it contained every possibly relevant wordlist extracted from previous leaked content, provided by everyday cracking tools, and created by custom word list generators. (darknet.org.uk)
  • The aim of this dictionary is to make such a body of work more accessible by providing an alphabetical list of key terms and concepts. (springer.com)
  • Bulk also influences the size of the word list for unabridged dictionaries. (britannica.com)
  • Bergenholtz, Tarp and Wiegand ( 1999 ) develop the notion of data distribution structure which offers lexicographers more space and latitude to go beyond the central list in the provision of dictionary data. (springer.com)
  • Using an overcomplete dictionary that contains prototype signal-atoms, signals are described by sparse linear combinations of these atoms. (psu.edu)
  • K-SVD is an iterative method that alternates between sparse coding of the examples based on the current dictionary and a process of updating the dictionary atoms to better fit the data. (psu.edu)
  • We develop a two-dimensional travel time tomography method, which regularizes the inversion by modeling groups of slowness pixels from discrete slowness maps, called patches, as sparse linear combinations of atoms from a dictionary. (ucsd.edu)
  • developerWorks provides tutorials, articles and other technical resources to help you grow your development skills on a wide variety of topics and products. (ibm.com)
  • Research Guides Librarian recommended resources & research tips tailored to your topic. (washington.edu)
  • Besides MOD, K-SVD, and other standard algorithms, it provides the significant dictionary learning problem variations, such as regularization, incoherence enforcing, finding an economical size, or learning adapted to specific problems like classification. (springer.com)
  • If students attended school prior to coming to the U.S., they may have already studied topics that are being covered in their content area classes. (ldonline.org)
  • With its wide-ranging description of different areas of microbiology, the Dictionary of Microbiology and Molecular Biology, Third Edition, Revised is an indispensable reference for every researcher, lecturer and student. (wiley.com)
  • Inspired by queries based on current events including the Trump family, Russia scandals, and a rash of celebrities being accused of sexual misconduct, the reference website Dictionary.com has named "complicit" its word of the year for 2017. (latimes.com)
  • This is done through design features that encourage learners to appreciate the educational value of dictionaries while facilitating efficient and optimum use of the dictionaries. (springer.com)
  • 2014 ), typifies school dictionaries in which lexicographers go beyond addressing learners' educational needs regarding language and other school subjects to integrate dictionary pedagogy that may prove beneficial in the long-term development of dictionary skills and dictionary culture. (springer.com)
  • Before we get to the dictionary itself, it is important to understand that most animals use a universal code based on three aspects of the sounds they make: namely pitch, duration, and frequency (or repetition rate). (psychologytoday.com)
  • LANZHOU - Authorities with China's national social sciences fund have earmarked 800,000 yuan ($128,000) for the compilation of a dictionary on Tibetan Buddhism, compilers said Saturday. (chinadaily.com.cn)
  • As a system of library classification the DDC is "arranged by discipline, not subject", so a topic like clothing is classed based on its disciplinary treatment (psychological influence of clothing at 155.95, customs associated with clothing at 391, and fashion design of clothing at 746.92) within the conceptual framework. (wikipedia.org)