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Mining protein networks for synthetic genetic interactions

Sri R Paladugu, Shan Zhao, Animesh Ray and Alpan Raval*

BMC Bioinformatics 2008, 9:426 doi:10.1186/1471-2105-9-426

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Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters

Yuehua Zhang, Bo Li, Pradip K Srimani, Xuewen Chen, Feng Luo Proteome Science 2012, 10(Suppl 1):S4 (21 June 2012)

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Research article   Open Access

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

Zhu-Hong You, Zheng Yin, Kyungsook Han, De-Shuang Huang, Xiaobo Zhou BMC Bioinformatics 2010, 11:343 (24 June 2010)

Abstract | Full text | PDF | PubMed | Cited on BioMed Central

Research article   Open Access

Human synthetic lethal inference as potential anti-cancer target gene detection

Nuria Conde-Pueyo, Andreea Munteanu, Ricard V Solé, Carlos Rodríguez-Caso BMC Systems Biology 2009, 3:116 (16 December 2009)

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Towards accurate imputation of quantitative genetic interactions

Igor Ulitsky, Nevan J Krogan, Ron Shamir Genome Biology 2009, 10:R140 (10 December 2009)

Abstract | Full text | PDF | PubMed | Cited on BioMed Central |  Editor’s summary

A new method for calculating quantitative genetic interactions allows for the inference of 190,000 new genetic interactions in Saccharomyces cerevisae.

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