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» Validation of protein models by a neural network approach
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CIMCA
2005
IEEE
14 years 1 months ago
An Accelerating Learning Algorithm for Block-Diagonal Recurrent Neural Networks
An efficient training method for block-diagonal recurrent neural networks is proposed. The method modifies the RPROP algorithm, originally developed for static models, in order to...
Paris A. Mastorocostas, Dimitris N. Varsamis, Cons...
ESANN
2008
13 years 9 months ago
A multiple testing procedure for input variable selection in neural networks
In this paper a novel procedure to select the input nodes in neural network modeling is presented and discussed. The approach is developed in a multiple testing framework and so it...
Michele La Rocca, Cira Perna
BMCBI
2007
139views more  BMCBI 2007»
13 years 7 months ago
XSTREAM: A practical algorithm for identification and architecture modeling of tandem repeats in protein sequences
Background: Biological sequence repeats arranged in tandem patterns are widespread in DNA and proteins. While many software tools have been designed to detect DNA tandem repeats (...
Aaron M. Newman, James B. Cooper
CMSB
2009
Springer
13 years 11 months ago
Control Strategies for the Regulation of the Eukaryotic Heat Shock Response
Abstract. Elevated temperatures cause proteins in living cells to misfold. They start forming larger and larger aggregates that can eventually lead to the cell's death. The he...
Elena Czeizler, Eugen Czeizler, Ralph-Johan Back, ...
ARTMED
2004
133views more  ARTMED 2004»
13 years 7 months ago
Bayesian network multi-classifiers for protein secondary structure prediction
Successful secondary structure predictions provide a starting point for direct tertiary structure modelling, and also can significantly improve sequence analysis and sequence-stru...
Víctor Robles, Pedro Larrañaga, Jos&...