Institution
Institute for Systems Biology
Nonprofit•Seattle, Washington, United States•
About: Institute for Systems Biology is a nonprofit organization based out in Seattle, Washington, United States. It is known for research contribution in the topics: Population & Proteomics. The organization has 1277 authors who have published 2777 publications receiving 353165 citations.
Topics: Population, Proteomics, Gene, Proteome, Systems biology
Papers published on a yearly basis
Papers
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TL;DR: Systems approaches can be used to predict immunogenicity and provide new mechanistic insights about vaccines as well as demonstrate an unappreciated role for CaMKIV in the regulation of antibody responses.
Abstract: Here we have used a systems biology approach to study innate and adaptive responses to vaccination against influenza in humans during three consecutive influenza seasons. We studied healthy adults vaccinated with trivalent inactivated influenza vaccine (TIV) or live attenuated influenza vaccine (LAIV). TIV induced higher antibody titers and more plasmablasts than LAIV did. In subjects vaccinated with TIV, early molecular signatures correlated with and could be used to accurately predict later antibody titers in two independent trials. Notably, expression of the kinase CaMKIV at day 3 was inversely correlated with later antibody titers. Vaccination of CaMKIV-deficient mice with TIV induced enhanced antigen-specific antibody titers, which demonstrated an unappreciated role for CaMKIV in the regulation of antibody responses. Thus, systems approaches can be used to predict immunogenicity and provide new mechanistic insights about vaccines.
722 citations
TL;DR: Proteomics and other complementary analysis methods are essential components of the emerging 'systems biology' approach that seeks to comprehensively describe biological systems through integration of diverse types of data and, in the future, to ultimately allow computational simulations of complex biological systems.
Abstract: Proteomics is the systematic study of the many and diverse properties of proteins in a parallel manner with the aim of providing detailed descriptions of the structure, function and control of biological systems in health and disease. Advances in methods and technologies have catalyzed an expansion of the scope of biological studies from the reductionist biochemical analysis of single proteins to proteome-wide measurements. Proteomics and other complementary analysis methods are essential components of the emerging 'systems biology' approach that seeks to comprehensively describe biological systems through integration of diverse types of data and, in the future, to ultimately allow computational simulations of complex biological systems.
720 citations
Institute for Systems Biology1, University of Texas MD Anderson Cancer Center2, Mayo Clinic3, Massachusetts Institute of Technology4, Van Andel Institute5, University of Pennsylvania6, Baylor College of Medicine7, Texas A&M University8, University of Texas Health Science Center at Houston9, Washington University in St. Louis10, Buck Institute for Research on Aging11, University of California, San Francisco12, University of Texas at Austin13, University of Washington14
TL;DR: These frequent DDR gene alterations in many human cancers have functional consequences that may determine cancer progression and guide therapy and a new machine-learning-based classifier developed from gene expression data allowed to identify alterations that phenocopy deleterious TP53 mutations.
706 citations
European Bioinformatics Institute1, Wellcome Trust2, University of Manchester3, University of Cambridge4, Swiss Institute of Bioinformatics5, École Polytechnique Fédérale de Lausanne6, Institute for Systems Biology7, University College Dublin8, Utrecht University9, University of Vienna10, Max Planck Society11, New York University12, Amgen13, University of California, Los Angeles14, Applied Biosystems15, Semel Institute for Neuroscience and Human Behavior16, Flanders Institute for Biotechnology17, University of New South Wales18, Scripps Research Institute19
TL;DR: The processes and principles underpinning the development of guidance modules for reporting the use of techniques such as gel electrophoresis and mass spectrometry are described and the ramifications for various interest groups such as experimentalists, funders, publishers and the private sector are discussed.
Abstract: Both the generation and the analysis of proteomics data are now widespread, and high-throughput approaches are commonplace. Protocols continue to increase in complexity as methods and technologies evolve and diversify. To encourage the standardized collection, integration, storage and dissemination of proteomics data, the Human Proteome Organization's Proteomics Standards Initiative develops guidance modules for reporting the use of techniques such as gel electrophoresis and mass spectrometry. This paper describes the processes and principles underpinning the development of these modules; discusses the ramifications for various interest groups such as experimentalists, funders, publishers and the private sector; addresses the issue of overlap with other reporting guidelines; and highlights the criticality of appropriate tools and resources in enabling 'MIAPE-compliant' reporting.
703 citations
TL;DR: Insights into the perturbative effects on genes involved in respiration, energy generation, and protein synthesis were obtained that would not have been apparent from measurements made at either the messenger RNA or protein level alone, illustrating the power of integrating different types of data obtained from the same sample for the comprehensive characterization of biological systems and processes.
702 citations
Authors
Showing all 1292 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Younan Xia | 216 | 943 | 175757 |
| Ruedi Aebersold | 182 | 879 | 141881 |
| David Haussler | 172 | 488 | 224960 |
| Steven P. Gygi | 172 | 704 | 129173 |
| Nahum Sonenberg | 167 | 647 | 104053 |
| Leroy Hood | 158 | 853 | 128452 |
| Mark H. Ellisman | 117 | 637 | 55289 |
| Wei Zhang | 112 | 1189 | 93641 |
| John Ralph | 109 | 442 | 39238 |
| Eric H. Davidson | 106 | 454 | 47058 |
| James R. Heath | 103 | 425 | 58548 |
| Alan Aderem | 99 | 246 | 46682 |
| Anne-Claude Gingras | 97 | 336 | 40714 |
| Trey Ideker | 97 | 306 | 72276 |
| Michael H. Gelb | 94 | 506 | 34714 |