Inferring mechanisms of compensation from E-MAP and SGA data using local search algorithms for max cut.
Journal of Computational Biology(2011)
摘要
A new method based on a mathematically natural local search framework for max cut is developed to uncover functionally coherent module and BPM motifs in high-throughput genetic interaction data. Unlike previous methods, which also consider physical protein-protein interaction data, our method utilizes genetic interaction data only; this becomes increasingly important as high-throughput genetic interaction data is becoming available in settings where less is known about physical interaction data. We compare modules and BPMs obtained to previous methods and across different datasets. Despite needing no physical interaction information, the BPMs produced by our method are competitive with previous methods. Biological findings include a suggested global role for the prefoldin complex and a SWR subcomplex in pathway buffering in the budding yeast interactome.
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关键词
sga data,max cut,biological finding,physical interaction data,genetic interaction data,previous method,inferring mechanism,physical protein-protein interaction data,bpm motif,physical interaction information,local search algorithm,swr subcomplex,new method,high-throughput genetic interaction data,protein protein interaction,high throughput,local search,genetics
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