Abstract Background Conventional differential gene expression analysis by methods such as students t-test, SAM, and Empirical Bayes often searches for statistically significant genes without considering the interactions among them. Network-based approaches provide a natural way to study these interactions and to investigate the rewiring interactions in disease versus control groups. In this paper, we apply weighted graphical LASSO (wgLASSO) algorithm to integrate a data-driven network model with prior biological knowledge (i.e., protein-protein interactions) for biological network inference. We propose a novel differentially weighted graphical LASSO (dwgLASSO) algorithm that builds group-specific networks and perform network-based differential gene expression analysis to select biomarker candidates by considering their topological differences between the groups. Results Through simulation, we showed that wgLASSO can achieve better performance in building biologically relevant networks than ...
Gene Expression Profiling Analysis of Bisphenol A-Induced Perturbation in Biological Processes in ER-Negative HEK293 Cells. . Biblioteca virtual para leer y descargar libros, documentos, trabajos y tesis universitarias en PDF. Material universiario, documentación y tareas realizadas por universitarios en nuestra biblioteca. Para descargar gratis y para leer online.
The heterogeneity of prostate cancers extends within clinical states and across states. At the extreme ends of the clinical spectrum are prognostically favorable localized tumors with a low biological potential for metastasis and tumors with a high propensity for early dissemination that are invariably lethal. These clinical phenotypes are related in part to the intrinsic biology of tumor cells and are reflected in the pattern of expression of specific genes. Using comprehensive gene expression analysis of tumor samples representing the nonmetastatic and metastatic phenotypes, we identified genes that were consistently and strongly differentially expressed and represent common and valid biological differences underlying clinical heterogeneity.. Few prior studies have used high-throughput gene expression analysis to study prostate cancer metastases. One reason is that well-preserved surgical tissue samples of metastatic prostate cancer are rare, which limits the availability of appropriate ...
Gene expression profiling has shown its ability to identify with high accuracy low cytogenetic risk acute myeloid leukemia such as acute promyelocytic leukemia and leukemias with t(8;21) or inv(16). The aim of this gene expression profiling study was to evaluate to what extent suboptimal samples with low leukemic blast load (range, 2-59%) and/or poor quality control criteria could also be correctly identified. Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n = 101) and/or poor quality control criteria (n = 10) (test set). With 10-marker classifiers, all training set samples as well as 97 of the 101 test
Osteoarthritis (OA) is characterized by alterations to subchondral bone as well as articular cartilage. Changes to bone in OA have also been identified at sites distal to the affected joint, which include increased bone volume fraction and reduced bone mineralization. Altered bone remodelling has been proposed to underlie these bone changes in OA. To investigate the molecular basis for these changes, we performed microarray gene expression profiling of bone obtained at autopsy from individuals with no evidence of joint disease (control) and from individuals undergoing joint replacement surgery for either degenerative hip OA, or fractured neck of femur (osteoporosis [OP]). The OP sample set was included because an inverse association, with respect to bone density, has been observed between OA and the low bone density disease OP. Compugen human 19K-oligo microarray slides were used to compare the gene expression profiles of OA, control and OP bone samples. Four sets of samples were analyzed, comprising 10
Since their first use nearly fifteen years ago [1], microarray gene expression profiling experiments have become a ubiquitous tool in the study of disease. The vast number of gene transcripts assayed by modern microarrays (105-106) has driven forward our understanding of biological processes tremendously, elucidating the genes and regulatory mechanisms that drive specific phenotypes. However, the high-dimensional data produced in these experiments--often comprising many more variables than samples and subject to noise--also presents analytical challenges.. The analysis of gene expression data can be broadly grouped into two categories: the identification of differentially expressed genes (or gene-sets) between two or more known conditions, and the unsupervised identification (clustering) of samples or genes that exhibit similar profiles across the data set. In the former case, each gene is tested individually for association with the phenotype of interest, adjusting at the end for the vast ...
A peripheral blood gene expression score is associated with plaque volume and phenotype by intravascular ultrasound with radiofrequency backscatter analysis: results from the ATLANTA study
TY - JOUR. T1 - Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for molecular subtype classification in diffuse large B-cell lymphoma. T2 - A report from the International DLBCL Rituximab-CHOP Consortium Program Study. AU - Visco, C.. AU - Li, Y.. AU - Xu-Monette, Z. Y.. AU - Miranda, R. N.. AU - Green, T. M.. AU - Li, Y.. AU - Tzankov, A.. AU - Wen, W.. AU - Liu, W. M.. AU - Kahl, B. S.. AU - DAmore, E. S.G.. AU - Montes-Moreno, S.. AU - Dybkær, K.. AU - Chiu, A.. AU - Tam, W.. AU - Orazi, A.. AU - Zu, Y.. AU - Bhagat, G.. AU - Winter, J. N.. AU - Wang, H. Y.. AU - ONeill, S.. AU - Dunphy, C. H.. AU - Hsi, E. D.. AU - Zhao, X. F.. AU - Go, R. S.. AU - Choi, W. W.L.. AU - Zhou, F.. AU - Czader, M.. AU - Tong, J.. AU - Zhao, X.. AU - Van Krieken, J. H.. AU - Huang, Q.. AU - Ai, W.. AU - Etzell, J.. AU - Ponzoni, M.. AU - Ferreri, A. J.M.. AU - Piris, M. A.. AU - Møller, M. B.. AU - Bueso-Ramos, C. E.. AU - Medeiros, L. ...
Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for molecular subtype classification in diffuse large B-cell lymphoma: a report from the International DLBCL Rituximab-CHOP Consortium Program Study.
Abstract: Association rules mining methods have been recently applied to gene expression data analysis to reveal relationships between genes and different conditions and features. However, not much effort has focused on detecting the relation between gene expression maps and related gene functions. Here we describe such an approach to mine association rules among gene functions in clusters of similar gene expression maps on mouse brain. The experimental results show that the detected association rules make sense biologically. By inspecting the obtained clusters and the genes having the gene functions of frequent itemsets, interesting clues were discovered that provide valuable insight to biological scientists. Moreover, discovered association rules can be potentially used to predict gene functions based on similarity of gene expression maps.. ...
TY - JOUR. T1 - Functional clustering of time series gene expression data by Granger causality. AU - Fujita, André. AU - Severino, Patricia. AU - Kojima, Kaname. AU - Sato, João R.. AU - Patriota, Alexandre G.. AU - Miyano, Satoru. PY - 2012/10/30. Y1 - 2012/10/30. N2 - Background: A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes.Results: In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its ...
Tahira, A. C., Kubrusly, M. S., Faria, M. F., Verjovski-Almeida, S., Reis, E. M., & Machado, M. C. C. (2010). Gene expression profiling reveals long intronic non-coding RNAs differentially expressed in pancreatic cancer and metastasis. Pancreas. Philadelphia ...
Purpose: Retinopathy of prematurity (ROP) is a common blinding disease caused by the abnormal growth of blood vessels in the retina of premature babies with low birth weight and low gestation period. However, the mechanisms and factors contributing to the progression of ROP are still unknown. The present study aimed to identify gene(s) responsible for ROP progression by a global gene expression profiling.. Methods: From a cohort of 600 subjects comprising ROP babies (n=350) and controls (n=250), 15 ROP babies at any stage (gestational age [GA] ≤ 35 weeks and/or birth weight [BW] ≤ 1700 g) and premature babies with no ROP (n=6) (GA ≤ 35 weeks and/or BW ≤ 1700 g) and full term babies of the same age and no ROP (n=3), were screened. RNA was isolated from 0.5-1 ml of blood using RNeasy mini kit from Qiagen and the purity and integrity of RNA was checked with Bioanalyzer 2100 (Agilent). Global gene expression profiling was performed by using Illumina bead Chip array having ~47,000 ...
TY - JOUR. T1 - Self-organizing latent lattice models for temporal gene expression profiling. AU - Zhang, Byoung Tak. AU - Yang, Jinsan. AU - Chi, Sung Wook. N1 - Funding Information: This work was supported by the Korean Government through BK21-IT, BrainTech, IMT2000 Bioinformatics and NRL Programs.. PY - 2003/7. Y1 - 2003/7. N2 - DNA microarrays are a high-throughput technology useful for functional genomics and gene expression analysis. While many microarray data are generated in sequence, most expression analysis tools are not utilizing the temporal information. Temporal expression profiling is important in many applications, including developmental studies, pathway analysis, and disease prognosis. In this paper, we develop a learning method designed for temporal gene expression profiling from massive DNA-microarray data. It attempts to learn probabilistic lattice maps of the gene expressions, which are then used for profiling the trajectories of temporal expressions of co-regulated genes. ...
Time-course gene expression profiles are frequently used to provide insight into the changes in cellular state over time and to infer the molecular pathways involved. When combined with large-scale molecular interaction networks, such data can provide information about the dynamics of cellular response to stimulus. However, few tools are currently available to predict a single active gene sub-network from time-course gene expression profiles. We introduce a tool, TimeXNet, which identifies active gene sub-networks with temporal paths using time-course gene expression profiles in the context of a weighted gene regulatory and protein-protein interaction network. TimeXNet uses a specialized form of the network flow optimization approach to identify the most probable paths connecting the genes with significant changes in expression at consecutive time intervals. TimeXNet has been extensively evaluated for its ability to predict novel regulators and their associated pathways within active gene sub-networks
Global gene expression analysis reveals pathway differences between teratogenic and non-teratogenic exposure concentrations of bisphenol A and 17β-estradiol in embryonic zebrafish.
The increased use of microarray expression profiling to study both the molecular biology of cancer and the cellular physiology of difficult-to-isolate cell types has led to a growing need for methods that allow the use of limiting quantities of RNA. This limitation has prompted the development of amplification methods that produce the quantities of RNA required for microarray analysis. Efforts have become increasingly focused upon developing a protocol that minimizes amplification bias, provides versatility, and reduces technical complexity. We evaluated the new protocol Transplex™ Whole Transcriptome Amplification (WTA) produced by Rubicon Genomics. The kit was tested on Human Reference RNA (Stratagene) and on RNA extracted from a renal tumor cell line. Reproducibility, sensitivity and reliability in calling differentially expressed genes were evaluated by both Real-Time PCR and GeneChip® technology (Affymetrix). We tested reproducibility by comparing the expression profiles provided by U133 ...
Association rules mining methods have been recently applied to gene expression data analysis to reveal relationships between genes and different conditions and features. However, not much effort has focused on detecting the relation between gene expression maps and related gene functions. Here we describe such an approach to mine association rules among gene functions in clusters of similar gene expression maps on mouse brain. The experimental results show that the detected association rules make sense biologically.
Rheumatoid arthritis (RA) is a heterogeneous disease and its underlying molecular mechanisms are still poorly understood. Because previous microarray studies have only focused on long-standing (LS) RA compared to osteoarthritis, we aimed to compare the molecular profiles of early and LS RA versus control synovia. Synovial biopsies were obtained by arthroscopy from 15 patients (4 early untreated RA, 4 treated LS RA and 7 controls, who had traumatic or mechanical lesions). Extracted mRNAs were used for large-scale gene-expression profiling. The different gene-expression combinations identified by comparison of profiles of early, LS RA and healthy synovia were linked to the biological processes involved in each situation. Three combinations of 719, 116 and 52 transcripts discriminated, respectively, early from LS RA, and early or LS RA from healthy synovia. We identified several gene clusters and distinct molecular signatures specifically expressed during early or LS RA, thereby suggesting the involvement
Seker, H. (2004) A Multi-Fuzzy Filtering Approach to Reliable Gene Expression Profile Analysis. Proceedings of the 2004 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, October 2004, pp. 37-40 ...
APC (Adenomatous polyposis coli) plays an important role in the pathogenesis of both familial and sporadic colorectal cancer. Patients carrying germline APC mutations develop multiple colonic adenomas at younger age and higher frequency than non-carrier cases which indicates that silencing of one APC allele may be sufficient to initiate the transformation process. To elucidate the biological dysregulation underlying adenoma formation we examined global gene expression profiles of adenomas and corresponding normal mucosa from an FAP patient. Differential expression of the most significant gene identified in this study was further validated by mRNA in situ hybridization, reverse transcriptase PCR and Northern blotting in different sets of adenomas, tumours and cancer cell lines. Eighty four genes were differentially expressed between all adenomas and corresponding normal mucosa, while only seven genes showed differential expression within the adenomas. The first group included pregnancy specific β-1
Background: Affymetrix GeneChip Array and Massively Parallel Signature Sequencing (MPSS) are two high throughput methodologies used to profile transcriptomes. Each method has certain strengths and weaknesses; however, no comparison has been made between the data derived from Affymetrix arrays and MPSS. In this study, two lineage-related prostate cancer cell lines, LNCaP and C4-2, were used for transcriptome analysis with the aim of identifying genes associated with prostate cancer progression. Methods: Affymetrix GeneChip array and MPSS analyses were performed. Data was analyzed with GeneSpring 6.2 and in-house perl scripts. Expression array results were verified with RT-PCR. Results: Comparison of the data revealed that both technologies detected genes the other did not. In LNCaP, 3,180 genes were only detected by Affymetrix and 1,169 genes were only detected by MPSS. Similarly, in C4-2, 4,121 genes were only detected by Affymetrix and 1,014 genes were only detected by MPSS. Analysis of the ...
With the genomic revolution and the era of targeted therapy, prognostic and predictive gene signatures are becoming increasingly important in clinical research. They are expected to assist prognosis assessment and therapeutic decision making. Notwithstanding, an evidence-based approach is needed to bring gene signatures from the laboratory to clinical practice. In early breast cancer, multiple prognostic gene signatures are commercially available without having formally reached the highest levels of evidence-based criteria. We discuss specific concepts for developing and validating a prognostic signature and illustrate them with contemporary examples in breast cancer. When a prognostic signature has not been developed for predicting the magnitude of relative treatment benefit through an interaction effect, it may be wishful thinking to test its predictive value. We propose that new gene signatures be built specifically for predicting treatment effects for future patients and outline an approach for this
Sensitivity and accuracy are key points when using microarrays to detect alterations in gene expression under different conditions. Critical to the acquisition of reliable results is the preparation of the RNA. In the field of virology, when analyzing the host cells reaction to infection, the often high representation of viral RNA (vRNA) within total RNA preparations from infected cells is likely to interfere with microarray analysis. Yet, this effect has not been investigated despite the many reports that describe gene expression profiling of virus-infected cells using microarrays. In this study we used coronaviruses as a model to show that vRNA indeed interferes with microarray analysis, decreasing both sensitivity and accuracy. We also demonstrate that the removal of vRNA from total RNA samples, by means of virus-specific oligonucleotide capturing, significantly reduced the number of false-positive hits and increased the sensitivity of the method as tested on different array platforms. We therefore
Purpose This article provides a review of the transcriptomic expression profiling studies that have been performed on meningiomas so far. We discuss some future prospects and challenges ahead in the field of gene expression profiling. Methods We performed a systematic search in the PubMed and EMBASE databases in May 2010 using the following search terms alone or in combination: meningioma, microarray analysis, oligonucleotide array sequence analysis, or gene expression profiling. Only original research articles in English that had used RNA hybridized to high-resolution microarray chips to generate gene expression profiles were included. Results We identified 13 articles matching the inclusion criteria. All studies had been performed during the last decade. Conclusions The main results of the studies can be grouped in three categories: (1) several groups have identified meningioma-specific genes and genes associated with the three WHO grades, and the main histological subtypes of grade I ...
Observation of gene expression changes implying gene regulations using a repetitive experiment in time course has become more and more important. However, there is no effective method which can handle such kind of data. For instance, in a clinical/biological progression like inflammatory response or cancer formation, a great number of differentially expressed genes at different time points could be identified through a large-scale microarray approach. For each repetitive experiment with different samples, converting the microarray datasets into transactional databases with significant singleton genes at each time point would allow sequential patterns implying gene regulations to be identified. Although traditional sequential pattern mining methods have been successfully proposed and widely used in different interesting topics, like mining customer purchasing sequences from a transactional database, to our knowledge, the methods are not suitable for such biological dataset because every transaction in
Background Parkinsons disease (PD) is affecting 5 million people worldwide, but the response mechanisms of the striatum are still unclear. Therefore, identification of gene expression alterations in...
Large mammals are capable of thermoregulation shortly after birth due to the presence of brown adipose tissue (BAT). The majority of BAT disappears after birth and is replaced by white adipose tissue (WAT). We analyzed the postnatal transformation of adipose in sheep with a time course study of the perirenal adipose depot. We observed changes in tissue morphology, gene expression and metabolism within the first two weeks of postnatal life consistent with the expected transition from BAT to WAT. The transformation was characterized by massively decreased mitochondrial abundance and down-regulation of gene expression related to mitochondrial function and oxidative phosphorylation. Global gene expression profiling demonstrated that the time points grouped into three phases: a brown adipose phase, a transition phase and a white adipose phase. Between the brown adipose and the transition phase 170 genes were differentially expressed, and 717 genes were differentially expressed between the transition and the
TY - JOUR. T1 - Mining cancer gene expression databases for latent information on intronic microRNAs. AU - Monterisi, Simona. AU - DArio, Giovanni. AU - Dama, Elisa. AU - Rotmensz, Nicole. AU - Confalonieri, Stefano. AU - Tordonato, Chiara. AU - Troglio, Flavia. AU - Bertalot, Giovanni. AU - Maisonneuve, Patrick. AU - Viale, Giuseppe. AU - Nicassio, Francesco. AU - Vecchi, Manuela. AU - Di Fiore, Pier Paolo. AU - Bianchi, Fabrizio. PY - 2015/2/1. Y1 - 2015/2/1. N2 - Around 50% of all human microRNAs reside within introns of coding genes and are usually co-transcribed. Gene expression datasets, therefore, should contain a wealth of miRNA-relevant latent information, exploitable for many basic and translational research aims. The present study was undertaken to investigate this possibility. We developed an in silico approach to identify intronic-miRNAs relevant to breast cancer, using public gene expression datasets. This led to the identification of a miRNA signature for aggressive breast ...
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BACKGROUND: Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially circumvented by instead matching gene expression signatures to signatures of other experiments. FINDINGS: To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700 Arabidopsis microarray experiments. CONCLUSIONS: Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro ...
The identification of a prognostic gene expression signature in breast cancer that is valid across multiple independent data sets and different microarray platforms is a challenging problem [1]. Recently, there have been reports of molecular prognostic and predictive signatures that were also valid in external independent cohorts [2-7]. One of these studies derived the prognostic signature from genes correlating with histological grade [4], while in [5] it was derived directly from correlations with clinical outcome data and was validated in estrogen receptor positive lymph node negative (ER+LN-) breast cancer. Another study validated a predictive score, based on 21 genes, for ER+LN-tamoxifen treated breast cancer [2]. These results are encouraging, yet, as explained recently in [8, 9], much larger cohort sizes may be needed before a consensus prognostic signature emerges. While the intrinsic subtype classification does appear to constitute a set of consensus signatures [7], it is also clear ...
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EpiRegNet aims to build a transcriptional regulatory network composing of histone modification and transcription factor binding in promoters and interactions between factors in these two fields ...
1. Chockalingm A, Campbell NR, Fodor JG. Worldwide epidemic of hypertension. Can J Cardio. 2006;22:553-555 2. Tomson J, Lip GYH. Blood Pressure demographic: nature or nurture…… genes or environment?. BMC Med. 2005;3:3 3. WHO. World Health Report 2002: Reducing Risks, Promoting Healthy life. Geneva: World Health Organization. 2002 4. Heller RA. et al. Discovery and analysis of inflammatory disease related genes using cDNA microarrays. Proc Nat Acad Sci. 1997;94:2150- 2155 5. Lockhart DJ, Dong H, Byrne MC, Follettie MT, Gallo MV, Chee MS, Mittmann M, Wang C, Kobayashi M, Horton H, Brown EL. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat Biotechnol. 1996;14:1675-80 6. Tzouvelekis A, Patlakas G, Bouros D. Application of Microarray Technology in pulmonary diseases. Respir Res. 2004;5:26 7. King HC, Sinha AA. Gene expression profile analysis by DNA microarrays: promise and pitfalls. JAMA. 2001;286:2280-2288 8. LI JJ. Inflammation in hypertension: primary ...
Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z-score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z-score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when ...
This project is an investigation of whether analysing subsets of time series gene expression data can give additional information about putatively co-regulated genes, compared to only using the whole time series. The original gene expression data set was partitioned into subsets and similarity was computed for both the whole timed series and subsets. Pearson correlation was used as similarity measure between gene expression profiles. The results indicate that analysing co-expression in subsets of gene expression data derives true-positive connections, with respect to co-regulation, that are not detected by only using the whole time series data. Unfortunately, with the actual data set, chosen similarity measure and partitioning of the data, randomly generated connections have the same amount of true-positives as the ones derived by the applied analysis. However, it is worth to continue further analysis of the subsets of gene expression data, which is based on the multi-factorial nature of gene ...
Preface. Acknowledgments.. 1 Introduction.. 1.1 Basic Terminology.. 1.1.1 The Central Dogma of Molecular Biology.. 1.1.2 Genome.. 1.1.3 Proteome.. 1.1.4 DNA (Deoxyribonucleic Acid).. 1.1.5 RNA (Ribonucleic Acid).. 1.1.6 mRNA (messenger RNA).. 1.1.7 Genetic Code.. 1.1.8 Gene.. 1.1.9 Gene Expression and the Gene Expression Level.. 1.1.10 Protein.. 1.2 Overlapping Areas of Research.. 1.2.1 Genomics.. 1.2.2 Proteomics.. 1.2.3 Bioinformatics.. 1.2.4 Transcriptomics and Other -omics.. 1.2.5 Data Mining.. 2 Basic Analysis of Gene Expression Microarray Data.. 2.1 Introduction.. 2.2 Microarray Technology.. 2.2.1 Spotted Microarrays.. 2.2.2 Affymetrix GeneChip® Microarrays.. 2.2.3 Bead-Based Microarrays.. 2.3 Low-Level Preprocessing of Assymetrix Microarrays.. 2.3.1 MAS5.. 2.3.2 RMA.. 2.3.3 GCRMA.. 2.3.4 PLIER.. 2.4 Public Repositories of Microarray Data.. 2.4.1 Microarray Gene Expression Data Society (MGED) Standards.. 2.4.2 Public Databases.. 2.4.2.1 Gene Expression Omnibus (GEO).. 2.4.2.2 ...
Report on emerging technologies for translational bioinformatics: a symposium on gene expression profiling for archival tissues. . Biblioteca virtual para leer y descargar libros, documentos, trabajos y tesis universitarias en PDF. Material universiario, documentación y tareas realizadas por universitarios en nuestra biblioteca. Para descargar gratis y para leer online.
CG000170_TechNote_BiologicalandTechnicalVariationinSingleCell3GeneExpressionExperiments_RevA_.pdf. Technical Note - Biological & Technical Variation in Single Cell Gene Expression Experiments. The Chromium Single Cell 3′ v2 Reagent Kits protocol (Document CG00052) produces Single Cell 3′ short-read sequencer compatible libraries. Technical and biological variation may be present in the experiment design, and may impact data interpretation. Potential sources of technical variation include running a sample on two separate microfluidic chips or at different well positions on the same chip, and or technical variation introduced by sequencing libraries on separate Illumina flowcells or sequencing lanes. This Technical Note examines the potential sources of technical and biological variation and their effects on single cell gene expression. These factors need to be considered when designing an experiment to minimize bias and generate reliable single cell gene expression data.. FOR USE WITH. ...
Background & objective: Microarray and next generation sequencing (NGS) data are the important sources to find helpful molecular patterns. Also, the great number of gene expression data increases the challenge of how to identify the biomarkers associated with cancer. The random forest (RF) is used to effectively analyze the problems of large-p and small-n. Therefore, RF can be used to select and rank the genes for the diagnosis and effective treatment of cancer. Methods: The microarray gene expression data of colon, leukemia, and prostate cancers were collected from public databases. Primary preprocessing was done on them using limma package, and then, the RF classification method was implemented on datasets separately in R software. Finally, the selected genes in each of the cancers were evaluated and compared with those of previous experimental studies and their functionalities were assessed in molecular cancer processes. Result: The RF method extracted very small sets of genes while it retained its
Breast cancer is the most common malignancy among women in the United States with the second highest incidence of cancer-related death following lung cancer. The decision-making process regarding adjuvant therapy is a time intensive dialogue between the patient and her oncologist. There are multiple tools that help individualize the treatment options for a patient. Population-based analysis with Adjuvant! Online and genomic profiling with Oncotype DX are two commonly used tools in patients with early stage, node-negative breast cancer. This case report illustrates a situation in which the population-based prognostic and predictive information differed dramatically from that obtained from genomic profiling and affected the patients decision. In light of this case, we discuss the benefits and limitations of these tools.
Gene set analysis methods use prior biological knowledge to analyze gene expression data. This prior knowledge takes the form of predefined groups of genes, linked through their biological function. Gene set analysis methods have been successfully applied in transversal studies, their results being more sensitive and interpretable than those of methods investigating genomic data one gene at a time. The time-course gene set analysis (TcGSA) introduced here is an extension of such gene set analysis to longitudinal data. This method identifies a priori defined groups of genes whose expression is not stable over time, taking into account the potential heterogeneity between patients and between genes. When biological conditions are compared, it identifies the gene sets that have different expression dynamics according to these conditions. Data from 2 studies are analyzed: data from an HIV therapeutic vaccine trial, and data from a recent study on influenza and pneumococcal vaccines. In both cases, TcGSA
For more than a decade, global gene expression profiling has been extensively used to elucidate the biology of human papillomaviruses (HPV) and their role in cervical- and head-and-neck cancers. Since 2008, the expression profiling of miRNAs has been reported in multiple HPV studies. Two major strategies have been employed in the gene and miRNA profiling studies: In the first approach, HPV positive tumors were compared to normal tissues or to HPV negative tumors. The second strategy relied on analysis of cell cultures transfected with single HPV oncogenes or with HPV genomes compared to untransfected cells considered as models for the development of premalignant and malignant transformations.. In this review, we summarize what we have learned from a decade of global expression profiling studies. We performed comprehensive analysis of the overlap of the lists of differentially expressed genes and microRNAs, in both tissue samples and cell culture based studies. The review focuses mainly on HPV16, ...
A meta-analysis was performed across six public microarray datasets for human small cell lung cancer (SCLC) comprising 365 samples across eight different platforms. Genes were ranked according to effect size and p-value for tumor versus control samples, and false discovery rates were calculated. The top scoring 48 genes that were significant by both methods, along with the 48 highest rated surface antigen genes, were used to populate a gene list for subsequent single cell evaluation. High throughput gene expression analysis was performed for 400 individual cells from one SCLC line (H446) using the Fluidigm microfluidic platform. Supervised machine learning was applied to identify transcriptionally-defined subgroups among these cells. The non-parametric Kolmogorov-Smirnov test was then used to determine those surface markers best able to distinguish each cluster. Individual cells from each group were then FACS-isolated, and clonogenicity was evaluated after 14 days in culture. Using these surface ...
Title: Definition of Genes and Paths Involved in Alzheimers Disease: Using Gene Expression Profiles and Chemical Genetics at the Mouse Brain Level. VOLUME: 7 ISSUE: 5. Author(s):Pu Wu and Yinghe Hu. Affiliation:Key Lab of Brain Functional GenomicsMOE STCSM; Shanghai Institute of Brain Functional Ge-nomics, East China Normal University, 3663 Zhongshan Road N. Shanghai, 200062, China.. Keywords:cDKO mice, SNAP-25, hypothalamus, neuronal plasticity, NMDA receptor. Abstract: Gene expression profiling of a number of distinct brain regions under different behavioral and biological states was analyzed using DNA microarray technology. These included hippocampal development, aging process, environ-mental enrichment, fear conditioning, and calorie restriction. Our results identified numerous genes and signal pathways that may play critical roles in learning and memory, brain aging and longevity. Furthermore, chemical genetic approach combined with gene expression profiling analysis was applied to study ...
Gene expression profiling classifies individual tumors by their gene expression patterns and may also describe and predict therapeutic resistance and sensitivity patterns. Profiling in several cancers, such as breast cancer, colon cancer, lymphoma, leukemia, and melanoma [3], has already identified molecular subclasses of tumors. Identification of tumor subtypes may be predictive for prognosis or response to drug therapy [6, 7, 28-31].. The potential of routine gene expression profiling to predict clinical outcomes for cancer patients has yet to be determined. The Evaluation of Genomic Applications in Practice and Prevention Working Group stated in 2009 that there was insufficient evidence to make a recommendation for or against the use of tumor gene expression profiles to improve outcomes in defined populations of women with breast cancer [32]. Clearly, more work needs to be done to translate promising research findings into clinically relevant results.. Comparison of FFPET sample-derived ...
Gene co-expression network analysis of transcriptome data has enabled the identification of key genes and important networks underlying complex production and disease traits. This study used weighted gene co-expression network analysis (WGCNA) approach to (1) detect modules or clusters of differentially expressed genes (DEG) with similar expression patterns in calf rumen transcriptome during pre- and post-weaning periods and (2) identify regulatory mechanisms linking gene modules to relevant phenotypes during the pre-weaning period (day 33 [d33]): weight gain (BWT_d33), average daily gain (ADG_d33), blood glucose (Glucose_d33) and β-hydroxybutyrate (BHB_d33) concentrations and post-weaning period (d96): weight gain (BWT_d96), average daily gain (ADG_d96), blood glucose (Glucose_d96) and β-hydroxybutyrate (BHB_d96) concentrations, dry matter intake (DMI_d96) and feed efficiency (FE_d96). Rumen tissues were collected from 16 calves on d33 and another 16 on d96 for whole transcriptome sequencing ...
TY - JOUR. T1 - Gene expression profiling on lung cancer outcome prediction. T2 - Present clinical value and future premise. AU - Sun, Zhifu. AU - Yang, Ping. N1 - Copyright: Copyright 2008 Elsevier B.V., All rights reserved.. PY - 2006/11. Y1 - 2006/11. N2 - DNA microarray has been widely used in cancer research to better predict clinical outcomes and potentially improve patient management. The new approach provides accurate tumor classification and outcome predictions, such as tumor stage, metastatic status, and patient survival, and offers some hope for individualized medicine. However, growing evidence suggests that gene-based prediction is not stable and little is known about the prediction power of gene expression profiles compared with well-known clinical and pathologic predictors. This review summarized up-to-date publications in microarray-based lung cancer clinical outcome prediction and conducted secondary analyses for those with sufficient sample sizes and associated clinical ...
Cervical cancer is the most common gynecologic malignant tumor, with a high incidence in 50-55-year-olds. This study aims to investigate the potential molecular mechanism of RRM2 for promoting the development of cervical cancer based on The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). RRM2 was found to be significant upregulated in cervical tissue (P,0.05) by extracting the expression of RRM2 from TCGA, GSE63514, GSE7410, GSE7803 and GSE9750. Survival analysis indicated that the overall survival was significantly worse in the patients with high-expression of RRM2 (P,0.05). The top 1000 positively/negatively correlated genes with RRM2 by Pearson Correlation test were extracted. The gene co-expression network by Weighted Gene Co-Expression Network Analysis (WGCNA) with these genes and the clinical characteristics (lymphocyte infiltration, monocyte infiltration, necrosis, neutrophil infiltration, the number of normal/stromal/tumor cells and the number of tumor nuclei) was ...
TY - JOUR. T1 - Single-cell gene expression profiling using FACS and qPCR with internal standards. AU - Porter, Joshua R.. AU - Telford, William G.. AU - Batchelor, Eric. N1 - Funding Information: We would like to thank V. Kapoor in the CCR ETIB Flow Cytometry Core for her aid in performing the cell sorting during the development of this protocol. We also thank M. Raffeld and the CCR LP Molecular Diagnostics Unit and J. Zhu and the NHLBI DNA Sequencing and Genomics Core for their aid in performing the qPCR during the development of this protocol. This research was supported by the Intramural Program of the NIH.. PY - 2017/2/25. Y1 - 2017/2/25. N2 - Gene expression measurements from bulk populations of cells can obscure the considerable transcriptomic variation of individual cells within those populations. Single-cell gene expression measurements can help assess the role of noise in gene expression, identify correlations in the expression of pairs of genes, and reveal subpopulations of cells that ...
Background: Soft tissue sarcomas are heterogeneous and a major complication in their management is that the existing classification scheme is not definitive and is still evolving. Leiomyosarcomas, a major histologic category of soft tissue sarcomas, are malignant tumours displaying smooth muscle differentiation. Although defined as a single group, they exhibit a wide range of clinical behaviour. We aimed to carry out molecular classification to identify new molecular subgroups with clinical relevance. Methods: We used gene expression profiling on 20 extra-uterine leiomyosarcomas and cross-study analyses for molecular classification of leiomyosarcomas. Clinical significance of the subgroupings was investigated. Results: We have identified two distinct molecular subgroups of leiomyosarcomas. One group was characterised by high expression of 26 genes that included many genes from the sub-classification gene cluster proposed by Nielsen et al. These sub-classification genes include genes that have ...
A DNA microarray is a solid support such as a glass slide, silicon chip or nylon membrane on which DNA molecules are attached at precise locations. Using DNA microarrays, the expression of tens of thousands of genes in a biological sample can be detected in one experiment. Emerging data suggests that the use of DNA microarrays can aid the differentiation of tumors with similar morphological appearance, predict patient outcome independently of conventional prognostic factors and select for response or resistance to specific anti-cancer therapies. DNA microarray technology thus has the potential to supplement standard diagnostic procedures in oncology and permit a more individualized approach to patient management. Prior to clinical application, however, this methodology must be simplified, standardized, evaluated in external quality assessment schemes and made available at relatively low costs. Most importantly, the preliminary, but promising, early findings must be validated by high-level ...
TY - JOUR. T1 - Homogeneous datasets of triple negative breast cancers enable the identification of novel prognostic and predictive signatures. AU - Karn, Thomas. AU - Pusztai, Lajos. AU - Holtrich, Uwe. AU - Iwamoto, Takayuki. AU - Shiang, Christine Y.. AU - Schmidt, Marcus. AU - Müller, Volkmar. AU - Solbach, Christine. AU - Gaetje, Regine. AU - Hanker, Lars. AU - Ahr, Andre. AU - Liedtke, Cornelia. AU - Ruckhäberle, Eugen. AU - Kaufmann, Manfred. AU - Rody, Achim. PY - 2011/12/29. Y1 - 2011/12/29. N2 - Background: Current prognostic gene signatures for breast cancer mainly reflect proliferation status and have limited value in triple-negative (TNBC) cancers. The identification of prognostic signatures from TNBC cohorts was limited in the past due to small sample sizes. Methodology/Principal Findings: We assembled all currently publically available TNBC gene expression datasets generated on Affymetrix gene chips. Inter-laboratory variation was minimized by filtering methods for both samples ...
Combining congenic mapping with microarray expression profiling offers an opportunity to establish functional links between genotype and phenotype for complex traits such as type 1 diabetes (T1D). We used high-density oligonucleotide arrays to measure the relative expression levels of |39,000 genes and ESTs in the NOD mouse (a murine model of T1D and other autoimmune conditions), four NOD-derived diabetes-resistant congenic strains, and two nondiabetic control strains. We developed a simple, yet general, method for measuring differential expression that provides an objective assessment of significance and used it to identify |400 gene expression differences and eight new candidates for the Idd9.1 locus. We also discovered a potential early biomarker for autoimmune hemolytic anemia that is based on different levels of erythrocyte-specific transcripts in the spleen. Overall, however, our results suggest that the dramatic disease protection conferred by six Idd loci (Idd3, Idd5.1, Idd5.2, Idd9.1, Idd9.2,
Table_6_Weighted Gene Co-expression Network Analysis Identifies Critical Genes for the Production of Cellulase and Xylanase in Penicillium oxalicum.XLSX
RNA Transcription Detected on Chromosomes 21 and 22 Using High Density Oligonucleotide Arrays. Thomas R. Gingeras, Affymetrix Inc., Santa Clara, CA. The first drafts of complete human genome sequence have brought with them the opportunities to map the RNA transcription patterns that are characteristic of each differentiated and undifferentiated cell type and characterize the sequence variations that underlie the phenotypic differences observed in the human population. By using the very high information content inherent in high-density oligonucleotide arrays it will be possible to map the locations of RNA transcription along the length of the entire human genome. Such a transcriptome map will provide information concerning: 1) the identification of novel transcription domains of the genome, 2) the predominant utilization of exon sequences during differentially spliced gene expression and 3) a empirically derived set of results which can be compared to the sequence annotation now being assembled ...
Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation - Time course gene expression experiments are a popular means to infer co-expression. Many methods have been proposed to cluster genes or to build networks based on similarity measures of their expression dynamics. In this paper we apply a correlation based approach to network reconstruction to three datasets of time series gene expression following system perturbation: 1) Conditional, Tamoxifen dependent, activation of the cMyc proto-oncogene in rat fibroblast; 2) Genomic response to nutrition changes in D. melanogaster; 3) Patterns of gene activity as a consequence of ageing occurring over a life-span time series (25y-90y) sampled from T-cells of human donors. We show that the three datasets undergo similar transitions from an uncorrelated regime to a positively or negatively correlated one that is symptomatic of a shift from a ground or basal state to a polarized state. In
Global gene expression profiling by DNA microarrays is an invaluable tool in biological research. However, existing labeling methods are time consuming and costly and therefore often limit the scale of microarray experiments and sample throughput. Here we introduce a new, fast, inexpensive method for direct random-primed fluorescent labeling of eukaryotic cDNA for gene expression analysis and compare the results obtained on the NimbleGen microarray platform with two other widely-used labeling methods, namely the NimbleGen-recommended double-stranded cDNA protocol and the indirect (aminoallyl) method. Two total RNA samples were labeled with each method and hybridized to NimbleGen expression arrays. Although all methods tested here provided similar global results and biological conclusions, the new direct random-primed cDNA labeling method provided slightly better correlation between replicates compared to the other methods and thus increased ability to find statistically significant differentially
An award for difficult RNA samples. Gene expression profiling using Next Generation Sequencing (NGS) is empowering an ever-increasing range of researchers to answer highly relevant biological and medical questions. At Lexogen, we are dedicated to developing innovative technologies for NGS and making these accessible for all scientists. With the Lexogen Research Award we wish to provide a chance for researchers to utilize more NGS. We ask you to submit a description of the project where you would use NGS and Lexogens RNA-Seq sample prep. The winners shall be given a product of Lexogen together with a free sequencing run and data analysis. The topic of this Research Award is High quality from low quality: Accurate gene expression profiling of low quality or FFPE samples. RNA sequencing is rapidly becoming the platform of choice for gene expression profiling projects. However, not all samples are created equal, and not all researchers have the luxury of working with high quality RNA for NGS library
Miscanthus lutarioriparius is a promising lignocellulosic feedstock for second-generation bioethanol production. However, the genomic resource for this species is relatively limited thus hampers our understanding of the molecular mechanisms underlying many important biological processes. In this study, we performed the first de novo transcriptome analysis of five tissues (leaf, stem, root, lateral bud and rhizome bud) of M. lutarioriparius with an emphasis to identify putative genes involved in rhizome development. Approximately 66 gigabase (GB) paired-end clean reads were obtained and assembled into 169,064 unigenes with an average length of 759 bp. Among these unigenes, 103,899 (61.5%) were annotated in seven public protein databases. Differential gene expression profiling analysis revealed that 4,609, 3,188, 1,679, 1,218 and 1,077 genes were predominantly expressed in root, leaf, stem, lateral bud, and rhizome bud, respectively. Their expression patterns were further classified into 12 distinct
The aims of the present study were to identify key genes and pathways associated with hepatocellular carcinoma (HCC) progression and predict compounds potentially associated with this type of carcinogenesis. The gene expression profile data of the GSE49515 dataset was obtained from the Gene Expression Omnibus database. The limma software package was used to identify the differentially expressed genes (DEGs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the Biological Networks Gene Ontology tool and the Database for Annotation, Visualization and Integrated Discovery, respectively. The Michigan Molecular Interactions database plugin within the Cytoscape software platform was used to perform protein‑protein interaction (PPI) network analysis. Chemical‑gene interaction data for HCC were obtained from the Comparative Toxicogenomics Database to evaluate the associations between drugs and specific genes. A total of 302 DEGs, including ...
TY - JOUR. T1 - Co-expression network analysis of peripheral blood transcriptome identifies dysregulated protein processing in endoplasmic reticulum and immune response in recurrent MDD in older adults. AU - Ciobanu, Liliana G.. AU - Sachdev, Perminder S.. AU - Trollor, Julian N.. AU - Reppermund, Simone. AU - Thalamuthu, Anbupalam. AU - Mather, Karen A.. AU - Cohen-Woods, Sarah Louise. AU - Stacey, David. AU - Toben, Catherine. AU - Schubert, Klaus Oliver. AU - Baune, Bernhard T.. PY - 2018/12. Y1 - 2018/12. N2 - The molecular factors involved in the pathophysiology of major depressive disorder (MDD) remain poorly understood. One approach to examine the molecular basis of MDD is co-expression network analysis, which facilitates the examination of complex interactions between expression levels of individual genes and how they influence biological pathways affected in MDD. Here, we applied an unsupervised gene-network based approach to a prospective experimental design using microarray ...
TY - JOUR. T1 - The effect of a single, temperature-sensitive mutation on global gene expression in Escherichia coli. AU - Li, Yong. AU - Cole, Kyle. AU - Altman, Sidney. N1 - Copyright: Copyright 2008 Elsevier B.V., All rights reserved.. PY - 2003/5/1. Y1 - 2003/5/1. N2 - High-density DNA microarrays have been used to explore the genomic profiling of gene expression of a defective Escherichia coli strain with a temperature-sensitive mutation in the protein component of RNase P. A novel gene cluster was discovered in which two of the genes are known substrates of RNase P. The expression pattern of essential genes and gene discovery from intergenic regions, for which other new transcripts are found, are also discussed.. AB - High-density DNA microarrays have been used to explore the genomic profiling of gene expression of a defective Escherichia coli strain with a temperature-sensitive mutation in the protein component of RNase P. A novel gene cluster was discovered in which two of the genes are ...
Gene expression in multiple individual cells from a tissue or culture sample varies according to cell-cycle, genetic, epigenetic and stochastic differences between the cells. However, single-cell differences have been largely neglected in the analysis of the functional consequences of genetic variation. Here we measure the expression of 92 genes affected by Wnt signaling in 1,440 single cells from 15 individuals to associate single-nucleotide polymorphisms (SNPs) with gene-expression phenotypes, while accounting for stochastic and cell-cycle differences between cells. We provide evidence that many heritable variations in gene function--such as burst size, burst frequency, cell cycle-specific expression and expression correlation/noise between cells--are masked when expression is averaged over many cells. Our results demonstrate how single-cell analyses provide insights into the mechanistic and network effects of genetic variability, with improved statistical power to model these effects on gene
The transcription factor c-Myb is required for modulation of progenitor cells in several tissues, including skeletal muscle and its upregulation is observed in many human being malignancies. in RMS sufferers. c-Myb could, therefore, lead to the growth phenotype by performing its inhibitory function in skeletal muscles difference. We also demonstrated that c-Myb proteins is normally abundant in migratory C2C12 myoblasts and its ectopic reflection potentiates cell motility. In overview, our outcomes implicate that metastatic properties of some RMS subtypes might end up being linked to c-Myb function. The transcription aspect c-Myb is normally needed for the regulations of progenitor cells in many tissue, including the hematopoietic program1,2, the adult human brain3, and colonic crypts4. It has a function in progenitor creation, keeping their expansion, migration, or family tree dedication. c-Myb appearance generally diminishes as progenitor cells differentiate. In truth, constitutive ...
Osaka-Dental-University-Susceptible rats (ODUS/Odu) are a useful animal model for human periodontal disease. Through comprehensive gene expression profiling, we aimed to evaluate the utility of ODUS/Odu-derived cells as an alternative to animal models for biomedical research into human periodontal disease. Using a GeneChip Rat Expression Array containing 15923 probes, the gene expression profiles of embryonic fibroblasts obtained from 13.5-day-old embryos of ODUS/Odu or control rats were comprehensively analyzed. This profiling revealed alterations in some genes that are likely to be related to periodontal disease in ODUS/Odu, based on a comparison with genes found in databases. Osteopontin (OPN), which is involved in immune defense reactions, bone metabolism and chronic inflammation, was among the genes whose expressions were significantly altered. Realtime RT-PCR analysis showed that the OPN mRNA level was increased by more than 5.8-fold in ODUS/Odu. Moreover, the expression of CD44, a ...
Autologous hematopoietic stem cell transplantation (aHSCT) has been used as a therapeutic approach in multiple sclerosis (MS). However, it is still unclear if the immune system that emerges from autologous CD34+ hematopoietic progenitor cells (HPC) of MS patients is pre-conditioned to re-develop the proinflammatory phenotype. The objective of this article is to compare the whole genome gene and microRNA expression signature in CD34+ HPC of MS patients and healthy donors (HD). CD34+ HPC were isolated from peripheral blood of eight MS patients and five HD and analyzed by whole genome gene expression and microRNA expression microarray. Among the differentially expressed genes (DEGs) only TNNT1 reached statistical significance (logFC=3.1, p,0.01). The microRNA expression was not significantly different between MS patients and HD. We did not find significant alterations of gene expression or microRNA profiles in CD34+ HPCs of MS patients. Our results support the use of aHSCT for treatment of MS. ...
The epithelial to mesenchymal transition (EMT) plays a key role in lung cancer progression and drug resistance. The dynamics and stability of gene expression patterns as cancer cells transition from E to M at a systems level and relevance to patient outcomes are unknown. Using comparative network and clustering analysis, we systematically analyzed time-series gene expression data from lung cancer cell lines H358 and A549 that were induced to undergo EMT. We also predicted the putative regulatory networks controlling EMT expression dynamics, especially for the EMT-dynamic genes and related these patterns to patient outcomes using data from TCGA. Example EMT hub regulatory genes were validated using RNAi. We identified several novel genes distinct from the static states of E or M that exhibited temporal expression patterns or periods during the EMT process that were shared in different lung cancer cell lines. For example, cell cycle and metabolic genes were found to be similarly down-regulated where
TY - JOUR. T1 - A Sequence Based Validation of Gene Expression Microarray Data. AU - Thallinger, Gerhard. AU - Obermayr, Eva. AU - Charoentong, Pornpimol. AU - Tong, Dan. AU - Trajanoski, Zlatko. AU - Zeillinger, Robert. PY - 2012. Y1 - 2012. UR - http://thescipub.com/ajb.toc. U2 - 10.3844/ajbsp.2012.1.9. DO - 10.3844/ajbsp.2012.1.9. M3 - Article. VL - 1. SP - 1. EP - 9. JO - American journal of bioinformatics. JF - American journal of bioinformatics. SN - 1948-9862. IS - 1. ER - ...
Early detection of breast cancer is key to successful treatment and patient survival. We have previously reported the potential use of gene expression profiling of peripheral blood cells for early detection of breast cancer. The aim of the present study was to refine these findings using a larger sample size and a commercially available microarray platform. Blood samples were collected from 121 females referred for diagnostic mammography following an initial suspicious screening mammogram. Diagnostic work-up revealed that 67 of these women had breast cancer while 54 had no malignant disease. Additionally, nine samples from six healthy female controls were included. Gene expression analyses were conducted using high density oligonucleotide microarrays. Partial Least Squares Regression (PLSR) was used for model building while a leave-one-out (LOO) double cross validation approach was used to identify predictors and estimate their prediction efficiency. A set of 738 probes that discriminated breast cancer
Temperature adaptation is one of the most important determinants of distribution and population size of organisms in nature. Recently, quantitative trait loci (QTL) mapping and gene expression profiling approaches have been used for detecting candidate genes for heat resistance. However, the resolution of QTL mapping is not high enough to examine the individual effects of various genes in each QTL. Heat stress-responsive genes, characterized by gene expression profiling studies, are not necessarily responsible for heat resistance. Some of these genes may be regulated in association with the heat stress response of other genes. To evaluate which heat-responsive genes are potential candidates for heat resistance with higher resolution than previous QTL mapping studies, we performed genome-wide deficiency screen for QTL for heat resistance. We screened 439 isogenic deficiency strains from the DrosDel project, covering 65.6% of the Drosophila melanogaster genome in order to map QTL for thermal resistance.
Developmental Anatomic Gene Expression Atlas (AGEA) The Allen Gene Expression Atlas (AGEA) for the Developing Mouse Brain is used to understand how voxels of the brain are related by gene expression (Correlation), and to find genes expressed at a particul
PubMed Central Canada (PMC Canada) provides free access to a stable and permanent online digital archive of full-text, peer-reviewed health and life sciences research publications. It builds on PubMed Central (PMC), the U.S. National Institutes of Health (NIH) free digital archive of biomedical and life sciences journal literature and is a member of the broader PMC International (PMCI) network of e-repositories.
TY - JOUR. T1 - Predicting response to docetaxel neoadjuvant chemotherapy for advanced breast cancers through genome-wide gene expression profiling. AU - Zembutsu, Hitoshi. AU - Suzuki, Yasuyo. AU - Sasaki, Aya. AU - Tsunoda, Tatsuhiko. AU - Okazaki, Minoru. AU - Yoshimoto, Masataka. AU - Hasegawa, Tadashi. AU - Hirata, Koichi. AU - Nakamura, Yusuke. PY - 2009. Y1 - 2009. N2 - Neoadjuvant chemotherapy with docetaxel for advanced breast cancer can improve the radicality for a subset of patients, but some patients suffer from severe adverse drug reactions without any benefit. To establish a method for predicting responses to docetaxel, we analyzed gene expression profiles of biopsy materials from 29 advanced breast cancers using a cDNA microarray consisting of 36,864 genes or ESTs, after enrichment of cancer cell population by laser microbeam microdissection. Analyzing eight PR (partial response) patients and twelve patients with SD (stable disease) or PD (progressive disease) response, we ...
Array-based comparative genomic hybridization (CGH) and gene expression profiling have become vital techniques for identifying molecular defects underlying genetic diseases. Regardless of the microarray platform, cyanine dyes (Cy3 and Cy5) are one of the most widely used fluorescent dye pairs for microarray analysis owing to their brightness and ease of incorporation, enabling high level of assay sensitivity. However, combining both dyes on arrays can become problematic during summer months when ozone levels rise to near 25 parts per billion (ppb). Under such conditions, Cy5 is known to rapidly degrade leading to loss of signal from either homebrew or commercial arrays. Cy5 can also suffer disproportionately from dye photobleaching resulting in distortion of (Cy5/Cy3) ratios used in copy number analysis. Our laboratory has been active in fluorescent dye research to find a suitable alternative to Cy5 that is stable to ozone and resistant to photo-bleaching. Here, we report on the development of such a
Purpose. human TM cells morphologically and started to specific many guns of TM cells while ceasing to specific pluripotency guns such as Nanog, April4, and Sox2. Functionally, the ability was created by these cells to phagocytose particles. Finally, publicity to dexamethasone or phorbol 12-myristate acetate triggered a specific boost in the creation and release of myocilin and matrix metalloproteinase-3, respectively, behavior quality of TM cells. Results. Our data show that iPSCs can be induced to assume a phenotype that resembles native TM cells in many important aspects. Not only do these cells represent a valuable research tool, but transplantation into glaucomatous eyes with elevated IOP may also restore function to the TM, resulting in re-establishment of IOP. … In order to induce iPSCs to differentiate into TM-like cells, iPSCs were cocultured with the human cell line hTM530 for up to 21 days. This immortalized cell line was used here since it grows at a very consistent rate and ...
Objective: To determine whether peripheral blood gene expression of patients with systemic lupus erythaematosus (SLE) correlates with disease activity measured using the SLE Disease Activity Index 2000 (SLEDAI-2K).. Methods: RNA was isolated from peripheral blood of 269 patients with SLE and profiled on a custom microarray. Hierarchical clustering and a heat map were used to categorise samples into major clusters based on gene expression pattern. Correlates, including demographic and disease-related characteristics such as SLEDAI-2K score, of the major sample clusters were compared using multivariate regression models.. Results: A set of 31 interferon (IFN)-regulated genes were seen to be driving the separations of samples into two clusters, one characterised by a relatively high IFN-regulated gene signature (n = 150) and the other by a relatively low IFN-regulated gene signature (n = 119). Disease activity measured using the SLEDAI-2K was significantly correlated with the high IFN gene ...
Gene expression network analysis and applications to immunology - We address the problem of using expression data and prior biological knowledge to identify differentially expressed pathways or groups of genes. Following an idea of Ideker et al. (2002), we construct a gene interaction network and search for high-scoring subnetworks. We make several improvements in terms of scoring functions and algorithms, resulting in higher speed and accuracy and easier biological interpretation. We also assign significance levels to our results, adjusted for multiple testing. Our methods are succesfully applied to three human microarray data sets, related to cancer and the immune system, retrieving several known and potential pathways. The method, denoted by the acronym GXNA (Gene eXpression Network Analysis) is implemented in software that is publicly available and can be used on virtually any microarray data set.
contribute to the vascular remodeling process associated with hypertension and atherosclerosis, the aims of this study were to assess the impact of 2-ME on pathophysiological pathways regulating SMC growth using transcriptional profiling. High-density oligonucleotide microarrays (Affymetrix Human Genome U_133 Plus 2.0 GeneChips) were used to identify differentially expressed genes in cultured human aortic SMCs treated with 2-ME (acutely, for 4 hrs, n=3; and chronically, for 48 hrs, n=3) and vehicle-treated time-matched controls (n=3 for each time point). Both single gene analysis (performed using Significance Analysis of Microarrays) as well as Gene Set Enrichment Analysis (GSEA, a computational method that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states) indicated downregulation of genes critically involved in mitotic spindle assembly and function in SMCs chronically treated with 2-ME when compared to ...
Summary: Genoscape is an open-source Cytoscape plug-in that visually integrates gene expression data sets from GenoScript, a transcriptomic database, and KEGG pathways into Cytoscape networks. The generated visualisation highlights gene expression changes and their statistical significance. The plug-in also allows one to browse GenoScript or import transcriptomic data from other sources through tab-separated text files. Genoscape has been successfully used by researchers to investigate the results of gene expression profiling experiments.. Availability: Genoscape is an open-source software freely available from the Genoscape webpage (http://www.pasteur.fr/recherche/unites/Gim/genoscape/). Installation instructions and tutorial can also be found at this URL.. Contact: [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.. ...
Purpose: To identify the novel gene signatures and molecular markers of nasopharyngeal carcinoma (NPC) by integrated bioinformatics analysis of multiple gene expression profiling datasets. Experimental Design: Seven published gene expression profiling studies and one of our unpublished works were reanalyzed to identify the common significantly dysregulated (CSD) genes in NPC. Overrepresentation analysis of cytogenetic bands, Gene Ontology (GO) categories, pathways were used to explore CSD genes functionally associated with carcinogenesis. The protein expressions of selected CSD genes were examined by immunohistochemistry on tissue microarrays, and the correlations of their expressions with clinical outcomes were evaluated. Results: Using the criteria (genes reported deregulated in more than one study), a total of 962 genes were identified as the CSD genes in NPC. Four up-regulated (BUB1B, CCND2, CENPF and MAD2L1) and two down-regulated (LTF and SLPI) genes were markedly reported in six studies. ...
Toxoplasma gondii is one of the most important apicomplexan parasites and infects one-third of the human population worldwide. Transformation between the tachyzoite and bradyzoite stages in the intermediate host is central to chronic infection and life-long risk. There have been some transcriptome studies on T. gondii; however, we are still early in our understanding of the kinds and levels of gene expression that occur during the conversion between stages. We used high-throughput RNA-sequencing data to assemble transcripts using genome-based and de novo strategies. The expression-level analysis of 6996 T. gondii genes showed that over half (3986) were significantly differentially expressed during stage conversion, whereas 2205 genes were upregulated, and 1778 genes were downregulated in tachyzoites compared with bradyzoites. Several important gene families were expressed at relatively high levels. Comprehensive functional annotation and gene ontology analysis revealed that stress response-related genes
TY - JOUR. T1 - MicroRNA expression profiling and Notch1 and Notch2 expression in minimal deviation adenocarcinoma of uterine cervix. AU - The Gynecological Pathology Study Group of the Korean Society of Pathologists. AU - Lee, Heejeong. AU - Kim, Kyu Rae. AU - Cho, Nam Hoon. AU - Hong, Sung Ran. AU - Jeong, Hoiseon. AU - Kwon, Sun Young. AU - Park, Kwang Hwa. AU - An, Hee Jung. AU - Kim, Tae Heon. AU - Kim, Insun. AU - Yoon, Hye Kyoung. AU - Suh, Kwang Sun. AU - Min, Ki Ouk. AU - Choi, Hyun Joo. AU - Park, Ji Young. AU - Yoo, Chong Woo. AU - Lee, Youn Soo. AU - Lee, Hee Jin. AU - Lee, Weon Sun. AU - Park, Chul Soo. AU - Lee, Yonghee. PY - 2014. Y1 - 2014. N2 - Background: MicroRNA (miRNA) expression is known to be deregulated in cervical carcinomas. However, no data is available about the miRNA expression pattern for the minimal deviation adenocarcinoma (MDA) of uterine cervix. We sought to detect deregulated miRNAs in MDA in an attempt to find the most dependable miRNA or their combinations to ...
TY - JOUR. T1 - Application of high-density DNA microarray to study smoke- and hydrogen peroxide-induced injury and repair in human bronchial epithelial cells. AU - Yoneda, Ken Y. AU - Mann-Jong Chang, Mary. AU - Chmiel, Ken. AU - Chen, Yin. AU - Wu, Reen. PY - 2003/8/1. Y1 - 2003/8/1. N2 - Recent advances in high-density DNA microarray technique allow the possibility to analyze thousands of genes simultaneously for their differential gene expression patterns in various biologic processes. Through clustering analysis and pattern recognition, the significance of these differentially expressed genes can be recognized and correlated with the biologic events that may take place inside the cell and tissue. High-density DNA microarray nylon membranes were used to explore gene expression and regulation associated with smoke-and hydrogen peroxide-induced injury and repair in differentiated human bronchial epithelial cells in vitro. At least three phases of change in gene expression could be recognized. ...