Threading with environment-specific score by artificial neural networks

Article

Mitchell, I., Jiang, N. and Wu, W. 2006. Threading with environment-specific score by artificial neural networks. Soft Computing. 10 (4), pp. 305-314. https://doi.org/10.1007/s00500-005-0488-6
TypeArticle
TitleThreading with environment-specific score by artificial neural networks
AuthorsMitchell, I., Jiang, N. and Wu, W.
Abstract

In this paper, a model named threading with environment-specific score (TES) is proposed to build a new threading score function with the use of artificial neural networks. It is demonstrated that the TES model can outperform a number of other models (e.g. those of residue contact potentials) which have the same level structure environment description. It is also simpler, which offers the potential for faster operation and hence has the potential to speed up searches for protein sequences with unknown structure and biochemical functions, which have increased exponentially with the rapid progress of the genome project.

Research GroupArtificial Intelligence group
PublisherSpringer
JournalSoft Computing
ISSN1432-7643
Electronic1433-7479
Publication dates
Online10 Oct 2005
PrintFeb 2006
Publication process dates
Deposited17 Oct 2008
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1007/s00500-005-0488-6
LanguageEnglish
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