bioRxiv preprint doi: https://doi.org/10.1101/598151; this version posted June 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Gene modules associated with human diseases revealed by network analysis Shisong Ma1,2*, Jiazhen Gong1†, Wanzhu Zuo1†, Haiying Geng1, Yu Zhang1, Meng Wang1, Ershang Han1, Jing Peng1, Yuzhou Wang1, Yifan Wang1, Yanyan Chen1 1. Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230027, China 2. School of Data Science, University of Science and Technology of China, Hefei, Anhui 230027, China * To whom correspondence should be addressed. Email:
[email protected] † These authors contribute equally. 1 bioRxiv preprint doi: https://doi.org/10.1101/598151; this version posted June 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. ABSTRACT Despite many genes associated with human diseases have been identified, disease mechanisms often remain elusive due to the lack of understanding how disease genes are connected functionally at pathways level. Within biological networks, disease genes likely map to modules whose identification facilitates etiology studies but remains challenging. We describe a systematic approach to identify disease-associated gene modules.