MCL-CAw: a refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure
1 Department of Computer Science, National University of Singapore, 117590, Singapore
2 Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
3 Qingdao Institute of Bioenergy and Bioprocess Technology, Qingdao 266101, China
BMC Bioinformatics 2010, 11:504 doi:10.1186/1471-2105-11-504Published: 12 October 2010
Additional files 1:
Additional figures and tables: Figures for core-attachment modularity and illustration of a predicted complex by MCL-CAw. Tables for setting of MCL-CAw parameters, and ranking of complex detection algorithms and affinity-scored networks.
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Additional files 2:
The MCL-CAw software package: The source code and installation details for the MCL-CAw software.
Format: ZIP Size: 3.8MB Download file