Oxypred: prediction and classification of oxygen-binding proteins.
IR@IMTECH: CSIR-Institute of Microbial Technology, Chandigarh
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| Title |
Oxypred: prediction and classification of oxygen-binding proteins.
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| Creator |
Muthukrishnan, S
Garg, Aarti Raghava, G.P.S. |
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| Subject |
QH301 Biology
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| Description |
This study describes a method for predicting and classifying oxygen-binding proteins. Firstly, support vector machine (SVM) modules were developed using amino acid composition and dipeptide composition for predicting oxygen-binding proteins, and achieved maximum accuracy of 85.5% and 87.8%, respectively. Secondly, an SVM module was developed based on amino acid composition, classifying the predicted oxygen-binding proteins into six classes with accuracy of 95.8%, 97.5%, 97.5%, 96.9%, 99.4%, and 96.0% for erythrocruorin, hemerythrin, hemocyanin, hemoglobin, leghemoglobin, and myoglobin proteins, respectively. Finally, an SVM module was developed using dipeptide composition for classifying the oxygen-binding proteins, and achieved maximum accuracy of 96.1%, 98.7%, 98.7%, 85.6%, 99.6%, and 93.3% for the above six classes, respectively. All modules were trained and tested by five-fold cross validation. Based on the above approach, a web server Oxypred was developed for predicting and classifying oxygen-binding proteins (available from http://www.imtech.res.in/raghava/oxypred/).
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| Publisher |
Elsevier Science
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| Date |
2007-12
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| Type |
Article
PeerReviewed |
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| Format |
application/pdf
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| Identifier |
http://crdd.osdd.net/open/614/1/raghava07.pdf
Muthukrishnan, S and Garg, Aarti and Raghava, G.P.S. (2007) Oxypred: prediction and classification of oxygen-binding proteins. Genomics, proteomics & bioinformatics / Beijing Genomics Institute, 5 (3-4). pp. 250-2. ISSN 1672-0229 |
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| Relation |
http://crdd.osdd.net/open/614/
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