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Open Access Research article

MCL-CAw: a refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

Sriganesh Srihari1, Kang Ning23 and Hon Wai Leong1

Author Affiliations

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:10.1186/1471-2105-11-504

Published: 12 October 2010

Additional files

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.

Format: PDF Size: 876KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

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

Open Data