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12

BIBE
2003
IEEE

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Prediction of Contact Maps Using Support Vector Machines

13 years 9 months ago

Prediction of Contact Maps Using Support Vector Machines

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Contact map prediction is of great interest for its application in fold recognition and protein 3D structure determination. In this paper we present a contact-map prediction algorithm that employs Support Vector Machines as the machine learning tool and incorporates various features such as sequence proﬁles and their conservation, correlated mutation analysis based on various amino acid physicochemical properties, and secondary structure. In addition, we evaluated the effectiveness of the different features on contact map prediction for different fold classes. On average, our predictor achieved a prediction accuracy of 0.2238 with

Ying Zhao, George Karypis

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Amino Acid Physicochemical | BIBE 2003 | Bioinformatics | Contact Map Prediction | Contact-map Prediction Algorithm |

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Added	04 Jul 2010
Updated	04 Jul 2010
Type	Conference
Year	2003
Where	BIBE
Authors	Ying Zhao, George Karypis

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