Literature DB >> 17041895

Genome-wide prediction of genetic interactions in a metazoan.

Shuichi Onami1, Hiroaki Kitano.   

Abstract

Genetic interactions provide information about genes and processes with overlapping functions in biological systems. For Saccharomyces cerevisiae, computational integration of multiple types of functional genomic data is used to generate genome-wide predictions of genetic interactions. However, this methodology cannot be applied to the vastly more complex genome of metazoans, and only recently has the first metazoan genome-wide prediction of genetic interactions been reported. The prediction for Caenorhabditis elegans was generated by computationally integrating functional genomic data from S. cerevisiae, C. elegans and Drosophila melanogaster. This achievement is an important step toward system-level understanding of biological systems and human diseases. (c) 2006 Wiley Periodicals, Inc.

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Year:  2006        PMID: 17041895     DOI: 10.1002/bies.20490

Source DB:  PubMed          Journal:  Bioessays        ISSN: 0265-9247            Impact factor:   4.345


  3 in total

1.  An integrative multi-network and multi-classifier approach to predict genetic interactions.

Authors:  Gaurav Pandey; Bin Zhang; Aaron N Chang; Chad L Myers; Jun Zhu; Vipin Kumar; Eric E Schadt
Journal:  PLoS Comput Biol       Date:  2010-09-09       Impact factor: 4.475

2.  A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network.

Authors:  Zhu-Hong You; Zheng Yin; Kyungsook Han; De-Shuang Huang; Xiaobo Zhou
Journal:  BMC Bioinformatics       Date:  2010-06-24       Impact factor: 3.169

Review 3.  Prediction of Genetic Interactions Using Machine Learning and Network Properties.

Authors:  Neel S Madhukar; Olivier Elemento; Gaurav Pandey
Journal:  Front Bioeng Biotechnol       Date:  2015-10-26
  3 in total

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