Hybrid Attractor Cellular Automata (HACA) for Addressing Major Problems in Bioinformatics

Research & Reviews: Journal of Engineering and Technology

article

Pokkuluri Kiran Sree¹  Inampudi Ramesh Babu²  SSSN Usha Devi Nedunuri³ 

[1] Department of CSE, BVC Engineering College;Department of CSE, Acharya Nagarjuna University;Department of CSE

关键词: Cellular Automata;    HACA;    Protein Structure;    Promoter Region;    Protein Coding Region;   

来源: Research & Reviews

【 摘 要 】

NLCA has grown as potential classifier for addressing major problems in bioinformatics. Lot of bioinformatics problems like predicting the protein coding region, finding the promoter region, prediction of the structure of protein and many other problems in bioinformatics can be addressed through Cellular Automata. Even though there are some prediction techniques addressing these problems, the approximate accuracy level is very less. An automated procedure was proposed with HACA (Hybrid Attractor Cellular Automata) which can address all these problems. Extensive experiments are conducted for reporting the accuracy of the proposed tool. The average accuracy of HACA when tested with ENCODE, BG570, HMR195, Fickett and Tongue, ASP67 datasets is 78%.

【 授权许可】

Unknown