Document Detail


Dimensionality of amino acid space and solvent accessibility prediction with neural networks.
MedLine Citation:
PMID:  16545617     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Solvent accessibility prediction from amino acid sequences has been pursued by several researchers. Such a prediction typically starts by transforming the amino acid category (or type) information into numerical representations. All twenty amino acids can be completely and uniquely represented by 20-dimensional vectors. Here, we investigate if the amino acid space defined in this way really requires twenty dimensions. We tried to develop corresponding representations in fewer dimensions. A method for searching optimal codification schema in an arbitrary space using neural networks was developed. The method is used to obtain optimal encoding of amino acids at various levels of dimensionality, and applied to optimize the amino acid codifications for the prediction of the solvent accessibility values of the proteins using feed-forward neural networks. The traditional 20-dimensional codification seems to be redundant in solving the solvent accessibility prediction problem, since a 1-dimensional codification is able to achieve almost the same degree of accuracy as the 20-dimensional codification. Optimal coding in much fewer dimensions could be used to make the predictions of accessible surface area with almost the same degree of accuracy as that obtained by a fully unique 20-dimensional coding. The 1-dimensional amino acid codification for solvent accessibility prediction obtained by a purely mathematical way based on neural networks is highly correlated with a physical property of the amino acids, namely their average solvent accessibility. The method developed to find the optimal codification is general, although the codification thus produced is dependent on the type of estimated property.
Authors:
Marcos J Araúzo-Bravo; Shandar Ahmad; Akinori Sarai
Related Documents :
15513337 - Effect of treatment with the molecular adsorbents recirculating system on arterial amin...
20381137 - Ragulator-rag complex targets mtorc1 to the lysosomal surface and is necessary for its ...
19497577 - Aminoglycoside antibiotics may interfere with microbial amino sugar analysis.
17448487 - Functionalized polymer colloids bearing primary amino groups.
22493737 - Retinol metabolism in the mollusk osilinus lineatus indicates an ancient origin for ret...
6625167 - Fluorometric determination of carbodiimides with trans-aconitic acid.
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2006-03-20
Journal Detail:
Title:  Computational biology and chemistry     Volume:  30     ISSN:  1476-9271     ISO Abbreviation:  Comput Biol Chem     Publication Date:  2006 Apr 
Date Detail:
Created Date:  2006-04-04     Completed Date:  2007-06-27     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101157394     Medline TA:  Comput Biol Chem     Country:  England    
Other Details:
Languages:  eng     Pagination:  160-8     Citation Subset:  IM    
Affiliation:
Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Fukuoka-ken 820-8502, Japan. marara@bse.kyutech.ac.jp
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Amino Acid Sequence
Amino Acids / chemistry*
Computational Biology
Neural Networks (Computer)*
Proteins / chemistry
Solvents
Chemical
Reg. No./Substance:
0/Amino Acids; 0/Proteins; 0/Solvents

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Listening to patients: choice in cardiac rehabilitation.
Next Document:  Transvaginal ultrasound for diagnosis of adenomyosis: a review.