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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: The first demonstration that Phaeocystis globosa does not "exude", but secretes microscopic gels is reported, which is a first of its kind.
Abstract: Almost half of the global photosynthetic activity is carried out in the ocean. During blooms, Phaeocystis can fix CO(2) at rates up to 40 g C m(-2) month(-1). Most of this carbon is released as polysaccharides. However, the cellular mechanism whereby this huge amount of organic material is exported into the seawater remains unknown. A vaguely defined process of "exudation" is believed responsible for the release of these biopolymers. Here we report the first demonstration that Phaeocystis globosa does not "exude", but secretes microscopic gels. Secretion is stimulated by blue light (lambda = 470+/-20 nm), and it is transduced by a characteristic intracellular Ca(2+) signal that precedes degranulation. The polysaccharides that form the matrix of these gels remain in condensed phase while stored in secretory vesicles. Upon exocytosis, the exopolymer matrix undergoes a characteristic phase transition accompanied by extensive swelling resulting in the formation of microscopic hydrated gels. Owing to their tangled topology, once released into the seawater, the polymers that make these gels can reptate (axially diffuse), interpenetrate neighboring gels, and anneal them together forming massive mucilage accumulations that are characteristic of Phaeocystis blooms. These gel masses can supply a rich source of microbial substrates, disperse in the seawater, and/or eventually sediment to the ocean floor.

70 citations

Journal ArticleDOI
TL;DR: The HUPO Human Proteome Project (HPP) has two overall goals: (1) stepwise completion of the protein parts list-the draft human proteome including confidently identifying and characterizing at least one protein product from each protein-coding gene, with increasing emphasis on sequence variants, post-translational modifications, and splice isoforms of those proteins.
Abstract: The HUPO Human Proteome Project (HPP) has two overall goals: (1) stepwise completion of the protein parts list—the draft human proteome including confidently identifying and characterizing at least one protein product from each protein-coding gene, with increasing emphasis on sequence variants, post-translational modifications (PTMs), and splice isoforms of those proteins; and (2) making proteomics an integrated counterpart to genomics throughout the biomedical and life sciences community. PeptideAtlas and GPMDB reanalyze all major human mass spectrometry data sets available through ProteomeXchange with standardized protocols and stringent quality filters; neXtProt curates and integrates mass spectrometry and other findings to present the most up to date authorative compendium of the human proteome. The HPP Guidelines for Mass Spectrometry Data Interpretation version 2.1 were applied to manuscripts submitted for this 2016 C-HPP-led special issue [www.thehpp.org/guidelines]. The Human Proteome presented as...

70 citations

Journal ArticleDOI
TL;DR: The power of integrating ‘omics’ and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system is illustrated.
Abstract: The mammalian immune system is a dynamic multiscale system composed of a hierarchically organized set of molecular, cellular, and organismal networks that act in concert to promote effective host defense. These networks range from those involving gene regulatory and protein-protein interactions underlying intracellular signaling pathways and single-cell responses to increasingly complex networks of in vivo cellular interaction, positioning, and migration that determine the overall immune response of an organism. Immunity is thus not the product of simple signaling events but rather nonlinear behaviors arising from dynamic, feedback-regulated interactions among many components. One of the major goals of systems immunology is to quantitatively measure these complex multiscale spatial and temporal interactions, permitting development of computational models that can be used to predict responses to perturbation. Recent technological advances permit collection of comprehensive datasets at multiple molecular and cellular levels, while advances in network biology support representation of the relationships of components at each level as physical or functional interaction networks. The latter facilitate effective visualization of patterns and recognition of emergent properties arising from the many interactions of genes, molecules, and cells of the immune system. We illustrate the power of integrating 'omics' and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system. We further discuss future possibilities for reconstruction of increasingly complex cellular- and organism-level networks and development of sophisticated computational tools for prediction of emergent immune behavior arising from the concerted action of these networks.

69 citations

Journal ArticleDOI
TL;DR: Gene ontology analysis revealed that the SOX2 interactome was enriched for GO terms GO:0030529 ribonucleoprotein complex and GO:0004386 helicase activity, suggesting a possible role forSOX2 in post‐transcriptional regulation in addition to its function as a transcription factor.
Abstract: SOX2 is a key gene implicated in maintaining the stemness of embryonic and adult stem cells that appears to re-activate in several human cancers including glioblastoma multiforme. Using immunoprecipitation (IP)/MS/MS, we identified 144 proteins that are putative SOX2 interacting proteins. Of note, SOX2 was found to interact with several heterogeneous nuclear ribonucleoprotein family proteins, including HNRNPA2B1, HNRNPA3, HNRNPC, HNRNPK, HNRNPL, HNRNPM, HNRNPR, HNRNPU, as well as other ribonucleoproteins, DNA repair proteins and helicases. Gene ontology (GO) analysis revealed that the SOX2 interactome was enriched for GO terms GO:0030529 ribonucleoprotein complex and GO:0004386 helicase activity. These findings indicate that SOX2 associates with the heterogeneous nuclear ribonucleoprotein complex, suggesting a possible role for SOX2 in post-transcriptional regulation in addition to its function as a transcription factor.

69 citations

Journal ArticleDOI
TL;DR: iCre1355 represents an experimentally validated genome-scale reconstruction of C. reinhardtii metabolism that should serve as a useful resource for studying the metabolic processes of this and related microalgae.
Abstract: Microalgae have reemerged as organisms of prime biotechnological interest due to their ability to synthesize a suite of valuable chemicals. To harness the capabilities of these organisms, we need a comprehensive systems-level understanding of their metabolism, which can be fundamentally achieved through large-scale mechanistic models of metabolism. In this study, we present a revised and significantly improved genome-scale metabolic model for the widely-studied microalga, Chlamydomonas reinhardtii. The model, iCre1355, represents a major advance over previous models, both in content and predictive power. iCre1355 encompasses a broad range of metabolic functions encoded across the nuclear, chloroplast and mitochondrial genomes accounting for 1355 genes (1460 transcripts), 2394 and 1133 metabolites. We found improved performance over the previous metabolic model based on comparisons of predictive accuracy across 306 phenotypes (from 81 mutants), lipid yield analysis and growth rates derived from chemostat-grown cells (under three conditions). Measurement of macronutrient uptake revealed carbon and phosphate to be good predictors of growth rate, while nitrogen consumption appeared to be in excess. We analyzed high-resolution time series transcriptomics data using iCre1355 to uncover dynamic pathway-level changes that occur in response to nitrogen starvation and changes in light intensity. This approach enabled accurate prediction of growth rates, the cessation of growth and accumulation of triacylglycerols during nitrogen starvation, and the temporal response of different growth-associated pathways to increased light intensity. Thus, iCre1355 represents an experimentally validated genome-scale reconstruction of C. reinhardtii metabolism that should serve as a useful resource for studying the metabolic processes of this and related microalgae.

69 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