Document Detail

Prediction of ATP/GTP-binding motif: a comparison of a perceptron type neural network and a consensus sequence method [corrected]
MedLine Citation:
PMID:  1946319     Owner:  NLM     Status:  MEDLINE    
Neural networks have been applied to a number of protein structure problems. In some applications their success has not been substantiated by a comparison with the performance of a suitable alternative statistical method on the same data. In this paper, a two-layer feed-forward neural network has been trained to recognize ATP/GTP-binding [corrected] local sequence motifs. The neural network correctly classified 78% of the 349 sequences used. This was much better than a simple motif-searching program. A more sophisticated statistical method was developed, however, which performed marginally better (80% correct classification) than the neural network. The neural network and the statistical method performed similarly on sequences of varying degrees of homology. These results do not imply that neural networks, especially those with hidden layers, are not useful tools, but they do suggest that two-layer networks in particular should be carefully tested against other statistical methods.
J D Hirst; M J Sternberg
Related Documents :
17139529 - Enhancement of the bulbocavernosus reflex during intraoperative neurophysiological moni...
11983929 - Prediction of proteasome cleavage motifs by neural networks.
18249909 - Multi-agent modeling of multiple fx-markets by neural networks.
10876349 - Including weight decay in the rescorla-wagner model avoids an unlikely prediction.
9205719 - On the independence of chromatic and achromatic stereopsis mechanisms.
521559 - A neural-counting model incorporating refractoriness and spread of excitation. i. appli...
17677999 - Ensemble averageability in network spectra.
18194169 - Colonization history of the swiss rhine basin by the bullhead (cottus gobio): inference...
22978889 - Computational modeling of phonatory dynamics in a tubular three-dimensional model of th...
Publication Detail:
Type:  Comparative Study; Journal Article    
Journal Detail:
Title:  Protein engineering     Volume:  4     ISSN:  0269-2139     ISO Abbreviation:  Protein Eng.     Publication Date:  1991 Aug 
Date Detail:
Created Date:  1991-12-13     Completed Date:  1991-12-13     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  8801484     Medline TA:  Protein Eng     Country:  ENGLAND    
Other Details:
Languages:  eng     Pagination:  615-23     Citation Subset:  IM    
Biomolecular Modelling Laboratory, Imperial Cancer Research Fund, Lincoln's Inn Fields, London, UK.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Adenosine Triphosphate*
Binding Sites
Consensus Sequence
Neural Networks (Computer)*
Protein Binding
Receptors, Purinergic / chemistry*
Sequence Homology, Nucleic Acid
Reg. No./Substance:
0/Receptors, Purinergic; 56-65-5/Adenosine Triphosphate
Erratum In:
Protein Eng 1993 Jul;6(5):549-54

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

Previous Document:  Simultaneous and multivariate alignment of protein sequences: correspondence between physicochemical...
Next Document:  Structural dynamics of calmodulin and troponin C.