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

We introduce a novel system for recognizing patterns of eye blinks for use in assistive technology interfaces and security systems. First, we present a blink-based interface for controlling devices. Well known songs are used as the cadence for the blinked patterns. Our system distinguishes between ten similar patterns with 99.0% accuracy. Second, we present a method for identifying individual people based on the characteristics of how they perform a specific pattern (their "blinkprint"). This technique could be used in conjunction with face recognition for security systems. We are able to distinguish between nine individuals with 82.02% accuracy based solely on how they blink the same pattern.

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