Threading with environment-specific score by artificial neural networks.

Mitchell, Ian ORCID: https://orcid.org/0000-0002-3882-9127, Jiang, Nan and Wu, Wendy Xinyu (2006) Threading with environment-specific score by artificial neural networks. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 10 (4) . pp. 305-314. ISSN 1432-7643 [Article] (doi:10.1007/s00500-005-0488-6)

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.

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