ICAR Research Data Repository for Knowledge Management
A neural-network based method for prediction of gamma-turns in proteins from multiple sequence alignment.
DIR@IMTECH: CSIR-Institute of Microbial Technology
View Archive Info| Field | Value | |
| Title |
A neural-network based method for prediction of gamma-turns in proteins from multiple sequence alignment.
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| Creator |
Kaur, Harpreet
Raghava, G.P.S. |
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| Subject |
QR Microbiology
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| Description |
In the present study, an attempt has been made to develop a method for predicting gamma-turns in proteins. First, we have implemented the commonly used statistical and machine-learning techniques in the field of protein structure prediction, for the prediction of gamma-turns. All the methods have been trained and tested on a set of 320 nonhomologous protein chains by a fivefold cross-validation technique. It has been observed that the performance of all methods is very poor, having a Matthew's Correlation Coefficient (MCC)
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| Publisher |
Wiley
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| Date |
2003-05
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| Type |
Article
PeerReviewed |
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| Format |
application/pdf
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| Identifier |
http://crdd.osdd.net/open/246/1/raghava2003.1.pdf
Kaur, Harpreet and Raghava, G.P.S. (2003) A neural-network based method for prediction of gamma-turns in proteins from multiple sequence alignment. Protein science : a publication of the Protein Society, 12 (5). pp. 923-9. ISSN 0961-8368 |
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| Relation |
http://onlinelibrary.wiley.com/doi/10.1110/ps.0241703/pdf
http://crdd.osdd.net/open/246/ |
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