Protein secondary structure prediction with bidirectional recurrent neural nets: Can weight updating for each residue enhance performance?

IFIP Advances in Information and Communication Technology

Volumn 339 AICT, Issue , 2010, Pages 128-137

  Agathocleous, Michalis ^a   Christodoulou, Georgia ^a   Promponas, Vasilis ^a   Christodoulou, Chris ^a   Vassiliades, Vassilis ^a   Antoniou, Antonis ^a  

^a UNIVERSITY OF CYPRUS   (Cyprus)

Author keywords

Bidirectional Recurrent Neural Networks; Bioinformatics and Computational Biology; Protein Secondary Structure Prediction

Indexed keywords

BACKPROPAGATION LEARNING ALGORITHM; BIDIRECTIONAL RECURRENT NEURAL NETWORKS; COMPUTATIONAL NEURAL NETWORKS; GLOBAL INFORMATIONS; MARKOV MODEL; NEURAL NET; ONLINE TRAINING; PERCENTAGE POINTS; POST PROCESSING; PROTEIN 3-D STRUCTURE; PROTEIN SECONDARY STRUCTURE PREDICTION; TRAINING PROCEDURES; WEIGHT UPDATE;

AMINO ACIDS; ARTIFICIAL INTELLIGENCE; BACKPROPAGATION ALGORITHMS; BIOINFORMATICS; FORECASTING; HIDDEN MARKOV MODELS; LEARNING ALGORITHMS; NETWORK ARCHITECTURE; PROTEINS; REINFORCEMENT LEARNING; THREE DIMENSIONAL; THREE DIMENSIONAL COMPUTER GRAPHICS;

RECURRENT NEURAL NETWORKS;

EID: 78549294177     PISSN: 18684238     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-16239-8_19     Document Type: Conference Paper

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