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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: Characterization of the Kap 121p-Nop1p and Kap121p-Sof1p interactions demonstrated that, in addition to lysine-rich nuclear localization signals (NLSs), Kap121 p recognizes a unique class of signals distinguished by the abundance of arginine and glycine residues and consequently termed rg-NLSS.
Abstract: In yeast there are at least 14 members of the β-karyopherin protein family that govern the movement of a diverse set of cargoes between the nucleus and cytoplasm. Knowledge of the cargoes carried by each karyopherin and insight into the mechanisms of transport are fundamental to understanding constitutive and regulated transport and elucidating how they impact normal cellular functions. Here, we have focused on the identification of nuclear import cargoes for the essential yeast β-karyopherin, Kap121p. Using an overlay blot assay and coimmunopurification studies, we have identified 30 putative Kap121p cargoes. Among these were Nop1p and Sof1p, two essential trans-acting protein factors required at the early stages of ribosome biogenesis. Characterization of the Kap121p-Nop1p and Kap121p-Sof1p interactions demonstrated that, in addition to lysine-rich nuclear localization signals (NLSs), Kap121p recognizes a unique class of signals distinguished by the abundance of arginine and glycine residues and consequently termed rg-NLSs. Kap104p is also known to recognize rg-NLSs, and here we show that it compensates for the loss of Kap121p function. Sof1p is also transported by Kap121p; however, its import can be mediated by a piggyback mechanism with Nop1p bridging the interaction between Sof1p and Kap121p. Together, our data elucidate additional levels of complexity in these nuclear transport pathways.

59 citations

Journal ArticleDOI
TL;DR: A genome-scale regulatory-metabolic model for MTB using the Probabilistic Regulation of Metabolism (PROM) framework is expanded and improves performance of knockout growth defect predictions compared to the original PROM MTB model, and it can successfully predict growth defects associated with TF overexpression.
Abstract: Mycobacterium tuberculosis (MTB) is the causative bacterium of tuberculosis, a disease responsible for over a million deaths worldwide annually with a growing number of strains resistant to antibiotics. The development of better therapeutics would greatly benefit from improved understanding of the mechanisms associated with MTB responses to different genetic and environmental perturbations. Therefore, we expanded a genome-scale regulatory-metabolic model for MTB using the Probabilistic Regulation of Metabolism (PROM) framework. Our model, MTBPROM2.0, represents a substantial knowledge base update and extension of simulation capability. We incorporated a recent ChIP-seq based binding network of 2555 interactions linking to 104 transcription factors (TFs) (representing a 3.5-fold expansion of TF coverage). We integrated this expanded regulatory network with a refined genome-scale metabolic model that can correctly predict growth viability over 69 source metabolite conditions and predict metabolic gene essentiality more accurately than the original model. We used MTBPROM2.0 to simulate the metabolic consequences of knocking out and overexpressing each of the 104 TFs in the model. MTBPROM2.0 improves performance of knockout growth defect predictions compared to the original PROM MTB model, and it can successfully predict growth defects associated with TF overexpression. Moreover, condition-specific models of MTBPROM2.0 successfully predicted synergistic growth consequences of overexpressing the TF whiB4 in the presence of two standard anti-TB drugs. MTBPROM2.0 can screen in silico condition-specific transcription factor perturbations to generate putative targets of interest that can help prioritize future experiments for therapeutic development efforts.

59 citations

Journal ArticleDOI
TL;DR: This protocol describes the use of PeptideAtlas, SRM atlas, and PASSEL, and highlights how to submit, search, collate and download data.
Abstract: PeptideAtlas, SRMAtlas, and PASSEL are Web-accessible resources to support discovery and targeted proteomics research. PeptideAtlas is a multi-species compendium of shotgun proteomic data provided by the scientific community; SRMAtlas is a resource of high-quality, complete proteome SRM assays generated in a consistent manner for the targeted identification and quantification of proteins; and PASSEL is a repository that compiles and represents selected reaction monitoring data, all in an easy-to-use interface. The databases are generated from native mass spectrometry data files that are analyzed in a standardized manner including statistical validation of the results. Each resource offers search functionalities and can be queried by user-defined constraints; the query results are provided in tables or are graphically displayed. PeptideAtlas, SRMAtlas, and PASSEL are publicly available freely via the Web site http://www.peptideatlas.org. In this protocol, we describe the use of these resources, we highlight how to submit, search, collate and download data. Curr. Protoc. Bioinform. 46:13.25.1-13.25.28. © 2014 by John Wiley & Sons, Inc. Keywords: discovery proteomics; targeted proteomics; selected reaction monitoring (SRM); data repository; data resource; complete proteome library

59 citations

Journal ArticleDOI
TL;DR: The results suggest that gangliosides act as co-receptors with Toll-like receptor 5 for FliC and promote hBD-2 expression via mitogen-activated protein kinase through phosphorylation in Caco-2 cells.

59 citations

Journal ArticleDOI
TL;DR: A synthesis of phenotypic and quantitative genomic traits is provided for bacteria and archaea, in the form of a scripted, reproducible workflow that standardizes and merges 26 sources.
Abstract: A synthesis of phenotypic and quantitative genomic traits is provided for bacteria and archaea, in the form of a scripted, reproducible workflow that standardizes and merges 26 sources. The resulting unified dataset covers 14 phenotypic traits, 5 quantitative genomic traits, and 4 environmental characteristics for approximately 170,000 strain-level and 15,000 species-aggregated records. It spans all habitats including soils, marine and fresh waters and sediments, host-associated and thermal. Trait data can find use in clarifying major dimensions of ecological strategy variation across species. They can also be used in conjunction with species and abundance sampling to characterize trait mixtures in communities and responses of traits along environmental gradients.

58 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