Genome Biology

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A strategy for extracting and analyzing large-scale quantitative epistatic interaction data

Sean R Collins, Maya Schuldiner, Nevan J Krogan and Jonathan S Weissman*

Genome Biology 2006, 7:R63 doi:10.1186/gb-2006-7-7-r63

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Proceedings   Open Access

A quantitative analysis of monochromaticity in genetic interaction networks

Chien-Hsiang Hsu, Tse-Yi Wang, Hsueh-Ting Chu, Cheng-Yan Kao, Kuang-Chi Chen BMC Bioinformatics 2011, 12(Suppl 13):S16 (30 November 2011)

Report   Open Access

Integrating multiple types of data to predict novel cell cycle-related genes

Lin Wang, Lin Hou, Minping Qian, Fangting Li, Minghua Deng BMC Systems Biology 2011, 5(Suppl 1):S9 (20 June 2011)

Method   Open Access Highly Accessed

Towards accurate imputation of quantitative genetic interactions

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

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

Methodology article   Open Access Highly Accessed

Accurate, precise modeling of cell proliferation kinetics from time-lapse imaging and automated image analysis of agar yeast culture arrays

Najaf A Shah, Richard J Laws, Bradley Wardman, Lue Zhao, John L Hartman BMC Systems Biology 2007, 1:3 (8 January 2007)

Automated image analysis of yeast on agar culture arrays provides accurate data on yeast culture biomass, allowing robust quantitative modeling of yeast cell proliferation.