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» Validation of protein models by a neural network approach
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ISMB
1994
13 years 9 months ago
Stochastic Motif Extraction Using Hidden Markov Model
In this paper, westudy the application of an ttMM(hidden Markov model) to the problem of representing protein sequencesby a stochastic motif. Astochastic protein motif represents ...
Yukiko Fujiwara, Minoru Asogawa, Akihiko Konagaya
ICANN
2005
Springer
14 years 1 months ago
Robust Structural Modeling and Outlier Detection with GMDH-Type Polynomial Neural Networks
Abstract. The paper presents a new version of a GMDH type algorithm able to perform an automatic model structure synthesis, robust model parameter estimation and model validation i...
Tatyana I. Aksenova, Vladimir Volkovich, Alessandr...
GECCO
2007
Springer
154views Optimization» more  GECCO 2007»
14 years 1 months ago
A novel ab-initio genetic-based approach for protein folding prediction
In this paper, a model based on genetic algorithms for protein folding prediction is proposed. The most important features of the proposed approach are: i) Heuristic secondary str...
Sergio Raul Duarte Torres, David Camilo Becerra Ro...
TR
2010
149views Hardware» more  TR 2010»
13 years 2 months ago
Health Condition Prediction of Gears Using a Recurrent Neural Network Approach
Abstract--The development of accurate health condition prediction approaches has been a key research topic in condition based maintenance (CBM) in recent years. However, current he...
Zhigang Tian, Ming J. Zuo
RECOMB
2005
Springer
14 years 8 months ago
Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition
Abstract. Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e. segmenta...
Yan Liu, Jaime G. Carbonell, Peter Weigele, Vanath...