Institution
Science Applications International Corporation
Company•McLean, Virginia, United States•
About: Science Applications International Corporation is a company organization based out in McLean, Virginia, United States. It is known for research contribution in the topics: Population & Virus. The organization has 7141 authors who have published 11747 publications receiving 696315 citations.
Topics: Population, Virus, Immune system, Cancer, Laser
Papers published on a yearly basis
Papers
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TL;DR: By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
Abstract: DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
31,015 citations
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TL;DR: The survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.
Abstract: Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.
13,102 citations
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TL;DR: DAMID is a web-accessible program that integrates functional genomic annotations with intuitive graphical summaries that assists in the interpretation of genome-scale datasets by facilitating the transition from data collection to biological meaning.
Abstract: The distributed nature of biological knowledge poses a major challenge to the interpretation of genome-scale datasets, including those derived from microarray and proteomic studies. This report describes DAVID, a web-accessible program that integrates functional genomic annotations with intuitive graphical summaries. Lists of gene or protein identifiers are rapidly annotated and summarized according to shared categorical data for Gene Ontology, protein domain, and biochemical pathway membership. DAVID assists in the interpretation of genome-scale datasets by facilitating the transition from data collection to biological meaning.
8,849 citations
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Drexel University1, Yeshiva University2, Roswell Park Cancer Institute3, Virginia Commonwealth University4, Van Andel Institute5, Science Applications International Corporation6, Massachusetts Institute of Technology7, Harvard University8, University of Miami9, Icahn School of Medicine at Mount Sinai10, University of Chicago11, Howard Hughes Medical Institute12, University of Geneva13, Stanford University14, University of Oxford15, University of North Carolina at Chapel Hill16, National Institutes of Health17
TL;DR: The Genotype-Tissue Expression (GTEx) project is described, which will establish a resource database and associated tissue bank for the scientific community to study the relationship between genetic variation and gene expression in human tissues.
Abstract: Genome-wide association studies have identified thousands of loci for common diseases, but, for the majority of these, the mechanisms underlying disease susceptibility remain unknown. Most associated variants are not correlated with protein-coding changes, suggesting that polymorphisms in regulatory regions probably contribute to many disease phenotypes. Here we describe the Genotype-Tissue Expression (GTEx) project, which will establish a resource database and associated tissue bank for the scientific community to study the relationship between genetic variation and gene expression in human tissues.
6,545 citations
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John N. Weinstein1, John N. Weinstein2, Eric A. Collisson3, Gordon B. Mills2 +376 more•Institutions (31)
TL;DR: The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA with a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages.
Abstract: The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.
5,294 citations
Authors
Showing all 7145 results
Name | H-index | Papers | Citations |
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David J. Hunter | 213 | 1836 | 207050 |
Elaine S. Jaffe | 156 | 828 | 112412 |
Ronald G. Crystal | 155 | 990 | 86680 |
Stephen J. Chanock | 154 | 1220 | 119390 |
Stephen J. O'Brien | 153 | 1062 | 93025 |
Martin A. Nowak | 148 | 591 | 94394 |
Seth M. Steinberg | 137 | 936 | 80148 |
Bruce R. Blazar | 132 | 1001 | 69622 |
Joost J. Oppenheim | 130 | 454 | 59601 |
Dan L. Longo | 125 | 697 | 56085 |
Sharon E. Straus | 120 | 879 | 72513 |
Warren Strober | 116 | 424 | 50247 |
Ruth Nussinov | 114 | 727 | 52320 |
Stefania Bandinelli | 113 | 450 | 55014 |
W. Marston Linehan | 112 | 568 | 50772 |