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Institution

Institute for Systems Biology

NonprofitSeattle, 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.


Papers
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Journal ArticleDOI
TL;DR: A search engine, ProbIDtree, is developed, which can identify multiple peptides from a CID spectrum generated by the concurrent fragmentation of multiple precursor ions in the same CID attempt.
Abstract: In MS/MS experiments with automated precursor ion, selection only a fraction of sequencing attempts lead to the successful identification of a peptide. A number of reasons may contribute to this situation. They include poor fragmentation of the selected precursor ion, the presence of modified residues in the peptide, mismatches with sequence databases, and frequently, the concurrent fragmentation of multiple precursors in the same CID attempt. Current database search engines are incapable of correctly assigning the sequences of multiple precursors to such spectra. We have developed a search engine, ProbIDtree, which can identify multiple peptides from a CID spectrum generated by the concurrent fragmentation of multiple precursor ions. This is achieved by iterative database searching in which the submitted spectra are generated by subtracting the fragment ions assigned to a tentatively matched peptide from the acquired spectrum and in which each match is assigned a tentative probability score. Tentatively matched peptides are organized in a tree structure from which their adjusted probability scores are calculated and used to determine the correct identifications. The results using MALDI-TOF-TOF MS/MS data demonstrate that multiple peptides can be effectively identified simultaneously with high confidence using ProbIDtree.

75 citations

Journal ArticleDOI
TL;DR: Integration of the quantitative proteomics with global protein interaction data using the Cytoscape platform led to the identification of several novel and liver-specific key regulatory components of the IFN response, which may be important in regulating the interplay between HCV, interferon and the host response to virus infection.
Abstract: Background: Interferons (IFNs) play a critical role in the host antiviral defense and are an essential component of current therapies against hepatitis C virus (HCV), a major cause of liver disease worldwide. To examine liver-specific responses to IFN and begin to elucidate the mechanisms of IFN inhibition of virus replication, we performed a global quantitative proteomic analysis in a human hepatoma cell line (Huh7) in the presence and absence of IFN treatment using the isotope-coded affinity tag (ICAT) method and tandem mass spectrometry (MS/MS). Results: In three subcellular fractions from the Huh7 cells treated with IFN (400 IU/ml, 16 h) or mock-treated, we identified more than 1,364 proteins at a threshold that corresponds to less than 5% false-positive error rate. Among these, 54 were induced by IFN and 24 were repressed by more than two-fold, respectively. These IFN-regulated proteins represented multiple cellular functions including antiviral defense, immune response, cell metabolism, signal transduction, cell growth and cellular organization. To analyze this proteomics dataset, we utilized several systems-biology datamining tools, including Gene Ontology via the GoMiner program and the Cytoscape bioinformatics platform.

75 citations

Journal ArticleDOI
TL;DR: It is shown in this qualitative and accessible discussion how the idea of a quasi-potential landscape and the theory of least-action-path offer a new formal understanding for computing the set of network nodes (molecular targets) that need to be targeted in concert in order to exit the cancer attractor.

75 citations

Journal ArticleDOI
TL;DR: The NE might better be considered as a discontinuous platform that promotes both gene activation and repression, and it is perhaps not surprising that many disease states are frequently associated with alterations in the NE.
Abstract: While often depicted as a static structure upon which proteinaceous factors bind to control gene expression, the genome is actually highly mobile and capable of exploring the complex domain architecture of the nucleus, which in turn controls genome maintenance and gene expression. Numerous genes relocate from the nuclear periphery to the nuclear interior upon activation and are hypothesized to interact with pre-assembled sites of transcription. In contrast to the nuclear interior, the nuclear periphery is widely regarded as transcriptionally silent. This is reflected by the preferential association of heterochromatin with the nuclear envelope. However, some activated genes are recruited to the nuclear periphery through interactions with nuclear pore complexes (NPCs) and NPC components are capable of preventing the spread of silent chromatin into adjacent regions of active chromatin, leading to the speculation that NPCs may facilitate the transition of chromatin between transcriptional states. Thus, the nuclear envelope (NE) might better be considered as a discontinuous platform that promotes both gene activation and repression. As such, it is perhaps not surprising that many disease states are frequently associated with alterations in the NE. Here we review the effects of the nuclear envelope and its constituents on chromatin organization and gene expression.

74 citations

Journal ArticleDOI
TL;DR: The mzQuantML data standard is developed, which can represent quantitative data about regions in two-dimensional retention time versus mass/charge space, peptides, and proteins and protein groups, and it offers limited support for small molecule (metabolomic) data.

74 citations


Authors

Showing all 1292 results

NameH-indexPapersCitations
Younan Xia216943175757
Ruedi Aebersold182879141881
David Haussler172488224960
Steven P. Gygi172704129173
Nahum Sonenberg167647104053
Leroy Hood158853128452
Mark H. Ellisman11763755289
Wei Zhang112118993641
John Ralph10944239238
Eric H. Davidson10645447058
James R. Heath10342558548
Alan Aderem9924646682
Anne-Claude Gingras9733640714
Trey Ideker9730672276
Michael H. Gelb9450634714
Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20233
202260
2021216
2020204
2019188
2018168