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: Small-RNA sequencing of samples from GBM patients demonstrated that both mature products of MIR-491 (miR-491-5p and -3p) are downregulated in tumors compared with the normal brain, and these products are a tumor suppressor gene that coordinately controls the key cancer hallmarks: proliferation, invasion and stem cell propagation.
Abstract: MIR-491 is commonly co-deleted with its adjacent CDKN2A on chromosome 9p21.3 in glioblastoma multiforme (GBM). However, it is not known whether deletion of MIR-491 is only a passenger event or has an important role. Small-RNA sequencing of samples from GBM patients demonstrated that both mature products of MIR-491 (miR-491-5p and -3p) are downregulated in tumors compared with the normal brain. The integration of GBM data from The Cancer Genome Atlas (TCGA), miRNA target prediction and reporter assays showed that miR-491-5p directly targets EGFR, CDK6 and Bcl-xL, whereas miR-491-3p targets IGFBP2 and CDK6. Functionally, miR-491-3p inhibited glioma cell invasion; overexpression of both miR-491-5p and -3p inhibited proliferation of glioma cell lines and impaired the propagation of glioma stem cells (GSCs), thereby prolonging survival of xenograft mice. Moreover, knockdown of miR-491-5p in primary Ink4a-Arf-null mouse glial progenitor cells exacerbated cell proliferation and invasion. Therefore, MIR-491 is a tumor suppressor gene that, by utilizing both mature forms, coordinately controls the key cancer hallmarks: proliferation, invasion and stem cell propagation.
87 citations
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TL;DR: In this paper, the information processing capacity of a complex dynamical system is reflected in the partitioning of its state space into disjoint basins of attraction, with state trajectories in each basin flowing towards their corresponding attractor.
Abstract: The information processing capacity of a complex dynamical system is reflected in the partitioning of its state space into disjoint basins of attraction, with state trajectories in each basin flowing towards their corresponding attractor. We introduce a novel network parameter, the basin entropy, as a measure of the complexity of information that such a system is capable of storing. By studying ensembles of random Boolean networks, we find that the basin entropy scales with system size only in critical regimes, suggesting that the informationally optimal partition of the state space is achieved when the system is operating at the critical boundary between the ordered and disordered phases.
86 citations
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Institute for Systems Biology1, European Bioinformatics Institute2, University Hospital of Lausanne3, University of Antwerp4, Ruhr University Bochum5, Protein Sciences6, Hong Kong University of Science and Technology7, Ghent University8, University of Cape Town9, University of Mainz10, University of Liverpool11
TL;DR: The Proteomics Standards Initiative is reviewed, synergies with other efforts such as the ProteomeXchange Consortium, the Human proteome Project, and the metabolomics community are described, and a look at future directions of the PSI are provided.
Abstract: The Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO) has now been developing and promoting open community standards and software tools in the field of proteomics for 15 years. Under the guidance of the chair, cochairs, and other leadership positions, the PSI working groups are tasked with the development and maintenance of community standards via special workshops and ongoing work. Among the existing ratified standards, the PSI working groups continue to update PSI-MI XML, MITAB, mzML, mzIdentML, mzQuantML, mzTab, and the MIAPE (Minimum Information About a Proteomics Experiment) guidelines with the advance of new technologies and techniques. Furthermore, new standards are currently either in the final stages of completion (proBed and proBAM for proteogenomics results as well as PEFF) or in early stages of design (a spectral library standard format, a universal spectrum identifier, the qcML quality control format, and the Protein Expression Interface (PROXI) web services Application Programming Interface). In this work we review the current status of all of these aspects of the PSI, describe synergies with other efforts such as the ProteomeXchange Consortium, the Human Proteome Project, and the metabolomics community, and provide a look at future directions of the PSI.
86 citations
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TL;DR: Protein profiling by SELDI is relatively easy to perform and it has great potential in prostate cancer diagnosis through pattern recognition, and Quantitative proteomics can potentially determine the identity of many biomarkers specific for prostate cancer.
86 citations
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TL;DR: In this paper, the tumor microenvironment of Gastroesophageal adenocarcinomas (GEAs) was characterized using RNAseq data and the Cancer Genome Atlas.
86 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 |