Literature DB >> 12662919

How reliable are experimental protein-protein interaction data?

Einat Sprinzak1, Shmuel Sattath, Hanah Margalit.   

Abstract

Data of protein-protein interactions provide valuable insight into the molecular networks underlying a living cell. However, their accuracy is often questioned, calling for a rigorous assessment of their reliability. The computation offered here provides an intelligible mean to assess directly the rate of true positives in a data set of experimentally determined interacting protein pairs. We show that the reliability of high-throughput yeast two-hybrid assays is about 50%, and that the size of the yeast interactome is estimated to be 10,000-16,600 interactions.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 12662919     DOI: 10.1016/s0022-2836(03)00239-0

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  114 in total

1.  Predicting protein complex membership using probabilistic network reliability.

Authors:  Saurabh Asthana; Oliver D King; Francis D Gibbons; Frederick P Roth
Journal:  Genome Res       Date:  2004-05-12       Impact factor: 9.043

2.  Protein networks, pleiotropy and the evolution of senescence.

Authors:  Daniel E L Promislow
Journal:  Proc Biol Sci       Date:  2004-06-22       Impact factor: 5.349

3.  Network motifs in integrated cellular networks of transcription-regulation and protein-protein interaction.

Authors:  Esti Yeger-Lotem; Shmuel Sattath; Nadav Kashtan; Shalev Itzkovitz; Ron Milo; Ron Y Pinter; Uri Alon; Hanah Margalit
Journal:  Proc Natl Acad Sci U S A       Date:  2004-04-12       Impact factor: 11.205

4.  Using manifold embedding for assessing and predicting protein interactions from high-throughput experimental data.

Authors:  Zhu-Hong You; Ying-Ke Lei; Jie Gui; De-Shuang Huang; Xiaobo Zhou
Journal:  Bioinformatics       Date:  2010-09-03       Impact factor: 6.937

5.  Evaluation of different biological data and computational classification methods for use in protein interaction prediction.

Authors:  Yanjun Qi; Ziv Bar-Joseph; Judith Klein-Seetharaman
Journal:  Proteins       Date:  2006-05-15

6.  Co-evolutionary analysis of domains in interacting proteins reveals insights into domain-domain interactions mediating protein-protein interactions.

Authors:  Raja Jothi; Praveen F Cherukuri; Asba Tasneem; Teresa M Przytycka
Journal:  J Mol Biol       Date:  2006-08-01       Impact factor: 5.469

7.  Modelling protein-protein interaction networks via a stickiness index.

Authors:  Natasa Przulj; Desmond J Higham
Journal:  J R Soc Interface       Date:  2006-10-22       Impact factor: 4.118

8.  Bacterial postgenomics: the promise and peril of systems biology.

Authors:  Garret Suen; Jimmy S Jakobsen; Barry S Goldman; Mitchell Singer; Anthony G Garza; Roy D Welch
Journal:  J Bacteriol       Date:  2006-09-22       Impact factor: 3.490

9.  Assessing and combining reliability of protein interaction sources.

Authors:  Sonia Leach; Aaron Gabow; Lawrence Hunter; Debra S Goldberg
Journal:  Pac Symp Biocomput       Date:  2007

10.  Integration of biological networks and gene expression data using Cytoscape.

Authors:  Melissa S Cline; Michael Smoot; Ethan Cerami; Allan Kuchinsky; Nerius Landys; Chris Workman; Rowan Christmas; Iliana Avila-Campilo; Michael Creech; Benjamin Gross; Kristina Hanspers; Ruth Isserlin; Ryan Kelley; Sarah Killcoyne; Samad Lotia; Steven Maere; John Morris; Keiichiro Ono; Vuk Pavlovic; Alexander R Pico; Aditya Vailaya; Peng-Liang Wang; Annette Adler; Bruce R Conklin; Leroy Hood; Martin Kuiper; Chris Sander; Ilya Schmulevich; Benno Schwikowski; Guy J Warner; Trey Ideker; Gary D Bader
Journal:  Nat Protoc       Date:  2007       Impact factor: 13.491

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.