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    
Abstract/OtherAbstract:
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.
Authors:
J D Hirst; M J Sternberg
Related Documents :
10075639 - Neural networks as "software sensors" in enzyme engineering.
16764509 - An oscillatory neural model of multiple object tracking.
14965879 - Genetically-designed neural networks for error reduction in an optimized biomechanical ...
12662489 - An efficient method to construct a radial basis function neural network classifier.
18276349 - Analysis and synthesis of a class of discrete-time neural networks described on hypercu...
15369059 - High-order neural network structure selection for function approximation applications u...
18358799 - Bone strength at the distal radius can be estimated from high-resolution peripheral qua...
3805449 - Sire evaluation for multiple binary responses when information is missing on some traits.
20726039 - Single-trial based independent component analysis on mismatch negativity in children.
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    
Affiliation:
Biomolecular Modelling Laboratory, Imperial Cancer Research Fund, Lincoln's Inn Fields, London, UK.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Adenosine Triphosphate*
Binding Sites
Consensus Sequence
Neural Networks (Computer)*
Protein Binding
Receptors, Purinergic / chemistry*
Sequence Homology, Nucleic Acid
Chemical
Reg. No./Substance:
0/Receptors, Purinergic; 56-65-5/Adenosine Triphosphate
Comments/Corrections
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.