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Enhanced protein domain discovery by using language modeling techniques from speech recognition.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Bateman, Alex Durbin, Richard Coin, Lachlan
Description	Author Affiliation: Coin L ( Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SA, United Kingdom.);
Abstract	Most modern speech recognition uses probabilistic models to interpret a sequence of sounds. Hidden Markov models, in particular, are used to recognize words. The same techniques have been adapted to find domains in protein sequences of amino acids. To increase word accuracy in speech recognition, language models are used to capture the information that certain word combinations are more likely than others, thus improving detection based on context. However, to date, these context techniques have not been applied to protein domain discovery. Here we show that the application of statistical language modeling methods can significantly enhance domain recognition in protein sequences. As an example, we discover an unannotated Tf_Otx Pfam domain on the cone rod homeobox protein, which suggests a possible mechanism for how the V242M mutation on this protein causes cone-rod dystrophy.
ISSN	00278424
e-ISSN	10916490
Journal	Proceedings of the National Academy of Sciences of the United States of America
Issue Number	8
Volume Number	100
Language	English
Publisher	National Academy of Sciences
Publisher Date	2003-04-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Protein Structure, Tertiary Algorithms Amino Acid Sequence Animals Biophysical Phenomena Biophysics Homeodomain Proteins Chemistry Genetics Markov Chains Mice Models, Molecular Models, Theoretical Molecular Sequence Data Nerve Tissue Proteins Otx Transcription Factors Point Mutation Sequence Homology, Amino Acid Speech Perception Trans-Activators Transcription Factors Research Support, Non-U.S. Gov't Multidisciplinary
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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