Published online 24 September 2004
Nucleic Acids Research, Vol. 32 No. 17 © Oxford University Press 2004; all rights reserved
HYPROSP: a hybrid protein secondary structure prediction algorithma knowledge-based approach
Institute of Information Science, Academia Sinica, Taipei, Taiwan
* To whom correspondence should be addressed. Tel: +886 2 27883799 ext. 1804; Fax: +886 2 27824814; Email: hsu{at}iis.sinica.edu.tw
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors
Received June 18, 2004; Revised August 4, 2004; Accepted September 2, 2004
We develop a knowledge-based approach (called PROSP) for protein secondary structure prediction. The knowledge base contains small peptide fragments together with their secondary structural information. A quantitative measure M, called match rate, is defined to measure the amount of structural information that a target protein can extract from the knowledge base. Our experimental results show that proteins with a higher match rate will likely be predicted more accurately based on PROSP. That is, there is roughly a monotone correlation between the prediction accuracy and the amount of structure matching with the knowledge base. To fully utilize the strength of our knowledge base, a hybrid prediction method is proposed as follows: if the match rate of a target protein is at least 80%, we use the extracted information to make the prediction; otherwise, we adopt a popular machine-learning approach. This comprises our hybrid protein structure prediction (HYPROSP) approach. We use the DSSP and EVA data as our datasets and PSIPRED as our underlying machine-learning algorithm. For target proteins with match rate at least 80%, the average Q3 of PROSP is 3.96 and 7.2 better than that of PSIPRED on DSSP and EVA data, respectively.
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H.-N. Lin, J.-M. Chang, K.-P. Wu, T.-Y. Sung, and W.-L. Hsu HYPROSP II-A knowledge-based hybrid method for protein secondary structure prediction based on local prediction confidence Bioinformatics, August 1, 2005; 21(15): 3227 - 3233. [Abstract] [Full Text] [PDF] |
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