| Paper: | MLSP-P2.1 | ||
| Session: | Bioinformatics and Biomedical Applications | ||
| Time: | Wednesday, May 19, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Machine Learning for Signal Processing: Bioinformatics Applications | ||
| Title: | PROTEIN SECONDARY STRUCTURE PREDICTION BASED ON THE AMINO ACIDS CONFORMATIONAL CLASSIFICATION AND NEURAL NETWORK TECHNIQUE | ||
| Authors: | Guang-Zheng Zhang; Chinese Academy of Sciences | ||
| De-Shuang Huang; Chinese Academy of Sciences | |||
| Hong-Qiang Wang; University of Science and Technology of China | |||
| Abstract: | In the paper, based on the 340 protein sequences got from theProtein Data Bank (PDB) and their corresponding secondarystructures, we grope the 20 different amino acids into three categories: Former, Breaker and Natural, according to their occurring frequencies in the three-state secondary structures: alpha-helix, beta-sheets and Coil, which reflect the intrinsic preference of that amino acid for a given type of secondary structure. Then we use this information and neural network technique to improve the protein secondary structure prediction (SSP) accuracy and get a better performance than the previous methods. | ||
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