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A method for finding communities of related genes
Open accessAbstract
We present a method for creating a network of gene co-occurrences from the literature and partitioning it into communities of related genes. The way in which our method identifies communities makes it likely that the component genes of each community will be related by their function. The method processes a large database of article abstracts, synthesizing information from many sources to shed light on groups of genes that have been shown to interact. It is a tool to be used by researchers in the biomedical sciences to swiftly search for known interactions and to provide insight into unexplored connections. The partitioning procedure is designed to be particularly applicable to large networks in which individual nodes may play a role in more than one community. In this paper, we explain the details of the method, in particular the partitioning process. We also apply the method to produce communities of genes related to colon cancer and show that the results are useful.
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Citations
Cited by
The Structure and Function of Complex Networks
Newman, M. E. J. (2003) · SIAM Review · doi:10.1137/s003614450342480 · Cited by 18,719
Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293
Finding community structure in very large networks
Clauset, A., Newman, M. E. J., & Moore, C. (2004) · Physical Review E · doi:10.1103/physreve.70.066111 · Cited by 7,390
Communities, modules and large-scale structure in networks
Newman, M. E. J. (2012) · Nature Physics · doi:10.1038/nphys2162 · Cited by 787
Community detection in networks: A multidisciplinary review
Javed, M. A., Younis, M. S., Latif, S., Qadir, J., & Baig, A. (2018) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2018.02.011 · Cited by 499
Metadata
- Authors
- Wilkinson, D. M., & Huberman, B. A.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2004-04-06
- Volume
- 101
- Issue
- suppl_1
- Pages
- 5241-5248
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2096631127
- Cited by
- 241
- References
- 0
- FWCI
- 7.22
- Type
- journal article
- Language
- en
- Open access
- green
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