Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm

Chan-Hoon Park; Soo-Jin Kim; Sun Kim; Dong-Yeon Cho; Byoung-Tak Zhang

doi:10.1109/BIBE.2007.4375559

7th IEEE International Conference on Bioinformatics and Bioengineering

Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm

Year: 2007

DOI Bookmark: 10.1109/BIBE.2007.4375559

Authors

Chan-Hoon Park, School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea. chpark@bi.snu.ac.kr
Soo-Jin Kim, Graduate Program in Bioinformatics, Seoul National University, Seoul 151-742, Korea. sjkim@bi.snu.ac.kr
Sun Kim, School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea. skim@bi.snu.ac.kr
Dong-Yeon Cho, School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea. dycho@bi.snu.ac.kr
Byoung-Tak Zhang, School of Computer Science and Engineering, Graduate Program in Bioinformatics, Seoul National University, Seoul 151-742, Korea. btzhang@bi.snu.ac.kr

Abstract

In this paper we describe a cellular automaton (CA) used to perform the watershed transform in N-D images. Our method is based on image integration via the Ford-Bellman shortest paths algorithm. Due to the local nature of CA algorithms we show that they are designed to run on massively parallel processors and therefore, be efficiently implemented on low cost consumer graphical processing units (GPUs).

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