Literature DB >> 15567862

A probabilistic functional network of yeast genes.

Insuk Lee1, Shailesh V Date, Alex T Adai, Edward M Marcotte.   

Abstract

A conceptual framework for integrating diverse functional genomics data was developed by reinterpreting experiments to provide numerical likelihoods that genes are functionally linked. This allows direct comparison and integration of different classes of data. The resulting probabilistic gene network estimates the functional coupling between genes. Within this framework, we reconstructed an extensive, high-quality functional gene network for Saccharomyces cerevisiae, consisting of 4681 (approximately 81%) of the known yeast genes linked by approximately 34,000 probabilistic linkages comparable in accuracy to small-scale interaction assays. The integrated linkages distinguish true from false-positive interactions in earlier data sets; new interactions emerge from genes' network contexts, as shown for genes in chromatin modification and ribosome biogenesis.

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Year:  2004        PMID: 15567862     DOI: 10.1126/science.1099511

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  289 in total

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Review 5.  Systems biology of ageing and longevity.

Authors:  Thomas B L Kirkwood
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6.  A genome-wide map of human genetic interactions inferred from radiation hybrid genotypes.

Authors:  Andy Lin; Richard T Wang; Sangtae Ahn; Christopher C Park; Desmond J Smith
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Review 7.  Methods for biological data integration: perspectives and challenges.

Authors:  Vladimir Gligorijević; Nataša Pržulj
Journal:  J R Soc Interface       Date:  2015-11-06       Impact factor: 4.118

8.  Discovery of protein interaction networks shared by diseases.

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Journal:  Pac Symp Biocomput       Date:  2007

Review 9.  Sequencing and beyond: integrating molecular 'omics' for microbial community profiling.

Authors:  Eric A Franzosa; Tiffany Hsu; Alexandra Sirota-Madi; Afrah Shafquat; Galeb Abu-Ali; Xochitl C Morgan; Curtis Huttenhower
Journal:  Nat Rev Microbiol       Date:  2015-04-27       Impact factor: 60.633

10.  Graphle: Interactive exploration of large, dense graphs.

Authors:  Curtis Huttenhower; Sajid O Mehmood; Olga G Troyanskaya
Journal:  BMC Bioinformatics       Date:  2009-12-14       Impact factor: 3.169

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