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Table of Contents

01 June 2017; volume 13, issue 6

  • Articles

Articles

  • Open Access
    Integration of over 9,000 mass spectrometry experiments builds a global map of human protein complexes
    Integration of over 9,000 mass spectrometry experiments builds a global map of human protein complexes
    1. Kevin Drew1,
    2. Chanjae Lee1,2,
    3. Ryan L Huizar1,2,
    4. Fan Tu1,2,
    5. Blake Borgeson1,2,4,
    6. Claire D McWhite1,2,
    7. Yun Ma2,3,
    8. John B Wallingford1,2 and
    9. Edward M Marcotte (marcotte{at}icmb.utexas.edu)*,1,2
    1. 1Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX, USA
    2. 2Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA
    3. 3The Otolaryngology Hospital, The First Affiliated Hospital of Sun Yat‐sen University Sun Yat‐sen University, Guangzhou, China
    4. 4Present Address: Recursion Pharmaceuticals Inc., Salt Lake City, UT, USA
    1. ↵*Corresponding author. Tel: +1 512 471 5435; E‐mail: marcotte{at}icmb.utexas.edu

    Integrating the largest‐scale mass spectrometry protein interaction datasets from a variety of human and animal cells and tissues in a machine‐learning framework generates the most comprehensive and accurate human protein complex map to date.

    Synopsis

    Integrating the largest‐scale mass spectrometry protein interaction datasets from a variety of human and animal cells and tissues in a machine‐learning framework generates the most comprehensive and accurate human protein complex map to date.

    • Thousands of new interactions are identified from affinity purification/mass spectrometry datasets by applying a weighted matrix model of interactions.

    • The resulting protein complex map strongly improves coverage of disease related genes and is examined in depth for ciliopathies.

    • Novel centriolar satellite members are predicted and experimentally validated, and the map reveals ANKRD55 to be a new member of the intraflagellar transport machinery.

    • cilia
    • ciliopathy
    • human interactome
    • mass spectrometry
    • protein complexes
    • proteomics

    Mol Syst Biol. (2017) 13: 932

    • Received December 7, 2016.
    • Revision received May 2, 2017.
    • Accepted May 12, 2017.
    • © 2017 The Authors. Published under the terms of the CC BY 4.0 license

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Kevin Drew, Chanjae Lee, Ryan L Huizar, Fan Tu, Blake Borgeson, Claire D McWhite, Yun Ma, John B Wallingford, Edward M Marcotte
    Published online 08.06.2017
    • Genome-Scale & Integrative Biology
    • Network Biology
    • Post-translational Modifications, Proteolysis & Proteomics
  • Open Access
    Biphasic response as a mechanism against mutant takeover in tissue homeostasis circuits
    Biphasic response as a mechanism against mutant takeover in tissue homeostasis circuits
    1. Omer Karin1 and
    2. Uri Alon (uri.alon{at}weizmann.ac.il)*,1
    1. 1Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
    1. ↵*Corresponding author. Tel: +972 8 934 4448; E‐mail: uri.alon{at}weizmann.ac.il

    Tissue homeostasis feedback circuits are inherently susceptible to mis‐sensing mutants. Biphasic signal response increases resistance to mis‐sensing mutants, at the cost of reduced dynamic stability.

    Synopsis

    Tissue homeostasis feedback circuits are inherently susceptible to mis‐sensing mutants. Biphasic signal response increases resistance to mis‐sensing mutants, at the cost of reduced dynamic stability.

    • Tissue feedback circuits are inherently susceptible to mutant invasion.

    • Biphasic signal response increases resistance to mis‐sensing mutants.

    • Resistance to mis‐sensing mutants trades‐off with dynamic stability.

    • Biphasic mechanisms explain observations in physiological circuits such as circuits of pancreatic beta cells, stem cells and immune cells.

    • calcium homeostasis
    • design principles
    • evolutionary dynamics
    • mathematical models of disease
    • stem‐cell homeostasis
    • tissue homeostasis

    Mol Syst Biol. (2017) 13: 933

    • Received February 24, 2017.
    • Revision received May 15, 2017.
    • Accepted May 22, 2017.
    • © 2017 The Authors. Published under the terms of the CC BY 4.0 license

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Omer Karin, Uri Alon
    Published online 26.06.2017
    • Quantitative Biology & Dynamical Systems
    • Signal Transduction
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In this Issue
Volume 13, Issue 6
01 June 2017
Molecular Systems Biology: 13 (6)
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