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The Scientific World Journal
Volume 2012, Article ID 315797, 14 pages
http://dx.doi.org/10.1100/2012/315797
Research Article

Pathway Detection from Protein Interaction Networks and Gene Expression Data Using Color-Coding Methods and A* Search Algorithms

1Department of Computer Science, National Tsing Hua University, Hsinchu 300, Taiwan
2Institute of Information Systems and Applications, National Tsing Hua University, Hsinchu 300, Taiwan

Received 9 September 2011; Accepted 17 October 2011

Academic Editor: Shanker Kalyana-Sundaram

Copyright © 2012 Cheng-Yu Yeh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

With the large availability of protein interaction networks and microarray data supported, to identify the linear paths that have biological significance in search of a potential pathway is a challenge issue. We proposed a color-coding method based on the characteristics of biological network topology and applied heuristic search to speed up color-coding method. In the experiments, we tested our methods by applying to two datasets: yeast and human prostate cancer networks and gene expression data set. The comparisons of our method with other existing methods on known yeast MAPK pathways in terms of precision and recall show that we can find maximum number of the proteins and perform comparably well. On the other hand, our method is more efficient than previous ones and detects the paths of length 10 within 40 seconds using CPU Intel 1.73GHz and 1GB main memory running under windows operating system.