Simple local search problems that are hard to solve
SIAM Journal on Computing
Integer Linear Programs and Local Search for Max-Cut
SIAM Journal on Computing
Efficient Maximal Cubic Graph Cuts (Extended Abstract)
ICALP '91 Proceedings of the 18th International Colloquium on Automata, Languages and Programming
Modularity and directionality in genetic interaction maps
Bioinformatics
Extracting between-pathway models from E-MAP interactions using expected graph compression
RECOMB'10 Proceedings of the 14th Annual international conference on Research in Computational Molecular Biology
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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.