Clique-based data mining for related genes in a biomedical database |
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| Authors: | Tsutomu Matsunaga Chikara Yonemori Etsuji Tomita Masaaki Muramatsu |
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| Institution: | (1) Research and Development Headquarters, NTT DATA Corporation, Tokyo 135-8671, Japan;(2) The Advanced Algorithms Research Laboratory, The University of Electro-Communications, Tokyo 182-8585, Japan;(3) Research and Development Initiative, Chuo University, Tokyo 112-8551, Japan;(4) Medical Research Institute, Tokyo Medical and Dental University, Tokyo 101-0062, Japan;(5) Research Institute, HuBit Genomix Inc, Tokyo 102-0092, Japan |
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| Abstract: | Background Progress in the life sciences cannot be made without integrating biomedical knowledge on numerous genes in order to help formulate
hypotheses on the genetic mechanisms behind various biological phenomena, including diseases. There is thus a strong need
for a way to automatically and comprehensively search from biomedical databases for related genes, such as genes in the same
families and genes encoding components of the same pathways. Here we address the extraction of related genes by searching
for densely-connected subgraphs, which are modeled as cliques, in a biomedical relational graph. |
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