Literature DB >> 18799807

Challenges and rewards of interaction proteomics.

Shoshana J Wodak1, Shuye Pu, James Vlasblom, Bertrand Séraphin.   

Abstract

The recent explosion of high throughput experimental technologies for characterizing protein interactions has generated large amounts of data describing interactions between thousands of proteins and producing genome scale views of protein assemblies. The systems level views afforded by these data hold great promise of leading to new knowledge but also involve many challenges. Deriving meaningful biological conclusions from these views crucially depends on our understanding of the approximation and biases that enter into deriving and interpreting the data. The challenges and rewards of interaction proteomics are reviewed here using as an example the latest comprehensive high throughput analyses of protein interactions in yeast.

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Year:  2008        PMID: 18799807     DOI: 10.1074/mcp.R800014-MCP200

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  29 in total

Review 1.  Proteomic analysis of stem cell differentiation and early development.

Authors:  Dennis van Hoof; Jeroen Krijgsveld; Christine Mummery
Journal:  Cold Spring Harb Perspect Biol       Date:  2012-03-01       Impact factor: 10.005

2.  Analysis of Human Nuclear Protein Complexes by Quantitative Mass Spectrometry Profiling.

Authors:  Katelyn E Connelly; Victoria Hedrick; Tiago Jose Paschoal Sobreira; Emily C Dykhuizen; Uma K Aryal
Journal:  Proteomics       Date:  2018-05-04       Impact factor: 3.984

3.  Categorizing biases in high-confidence high-throughput protein-protein interaction data sets.

Authors:  Xueping Yu; Joseph Ivanic; Vesna Memisević; Anders Wallqvist; Jaques Reifman
Journal:  Mol Cell Proteomics       Date:  2011-08-29       Impact factor: 5.911

4.  From evidence to inference: probing the evolution of protein interaction networks.

Authors:  Oliver Ratmann; Carsten Wiuf; John W Pinney
Journal:  HFSP J       Date:  2009-10-19

5.  In silico prediction of physical protein interactions and characterization of interactome orphans.

Authors:  Max Kotlyar; Chiara Pastrello; Flavia Pivetta; Alessandra Lo Sardo; Christian Cumbaa; Han Li; Taline Naranian; Yun Niu; Zhiyong Ding; Fatemeh Vafaee; Fiona Broackes-Carter; Julia Petschnigg; Gordon B Mills; Andrea Jurisicova; Igor Stagljar; Roberta Maestro; Igor Jurisica
Journal:  Nat Methods       Date:  2014-11-17       Impact factor: 28.547

Review 6.  Popular computational methods to assess multiprotein complexes derived from label-free affinity purification and mass spectrometry (AP-MS) experiments.

Authors:  Irina M Armean; Kathryn S Lilley; Matthew W B Trotter
Journal:  Mol Cell Proteomics       Date:  2012-10-15       Impact factor: 5.911

7.  A transcriptome-proteome integrated network identifies endoplasmic reticulum thiol oxidoreductase (ERp57) as a hub that mediates bone metastasis.

Authors:  Naiara Santana-Codina; Rafael Carretero; Rebeca Sanz-Pamplona; Teresa Cabrera; Emre Guney; Baldo Oliva; Philippe Clezardin; Omar E Olarte; Pablo Loza-Alvarez; Andrés Méndez-Lucas; Jose Carlos Perales; Angels Sierra
Journal:  Mol Cell Proteomics       Date:  2013-04-26       Impact factor: 5.911

8.  Protein networks reveal detection bias and species consistency when analysed by information-theoretic methods.

Authors:  Luis P Fernandes; Alessia Annibale; Jens Kleinjung; Anthony C C Coolen; Franca Fraternali
Journal:  PLoS One       Date:  2010-08-18       Impact factor: 3.240

Review 9.  Interaction proteomics of synapse protein complexes.

Authors:  Ka Wan Li; Patricia Klemmer; August B Smit
Journal:  Anal Bioanal Chem       Date:  2010-04-02       Impact factor: 4.142

Review 10.  From protein sequences to 3D-structures and beyond: the example of the UniProt knowledgebase.

Authors:  Ursula Hinz
Journal:  Cell Mol Life Sci       Date:  2009-12-31       Impact factor: 9.261

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