A Feature Selection Algorithm Based on Graph Theory and Random Forests for Protein Secondary Structure Prediction

Selection Algorithm ◽

Feature Selection Algorithm ◽

Ensemble of Bidirectional Recurrent Networks and Random Forests for Protein Secondary Structure Prediction

2020 International Conference on Systems, Signals and Image Processing (IWSSIP) ◽

10.1109/iwssip48289.2020.9145437 ◽

2020 ◽

Cited By ~ 1

Author(s):

Gabriel Bianchin de Oliveira ◽

Helio Pedrini ◽

Zanoni Dias

Keyword(s):

Secondary Structure ◽

Random Forests ◽

Structure Prediction ◽

Recurrent Networks ◽

Faculty Opinions recommendation of Protein secondary structure prediction using deep convolutional neural fields.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.726067888.793548469 ◽

2018 ◽

Author(s):

Patrice Koehl

Keyword(s):

Secondary Structure ◽

Structure Prediction ◽

Neural Fields ◽

Identification and application of the concepts important for accurate and reliable protein secondary structure prediction

Protein Science ◽

10.1002/pro.5560051116 ◽

1996 ◽

Vol 5 (11) ◽

pp. 2298-2310 ◽

Cited By ~ 299

Author(s):

Ross D. King ◽

Michael J.E. Sternberg

Keyword(s):

Secondary Structure ◽

Structure Prediction ◽

Protein Secondary Structure Prediction Using Support Vector Machines (SVMs)

2013 International Conference on Machine Intelligence and Research Advancement ◽

10.1109/icmira.2013.124 ◽

2013 ◽

Author(s):

Hitesh Shah

Keyword(s):

Support Vector Machines ◽

Secondary Structure ◽

Structure Prediction ◽

Support Vector ◽

Vector Machines

Protein Secondary Structure Prediction using Bayesian Inference method on Decision fusion algorithms

2007 IEEE International Parallel and Distributed Processing Symposium ◽

10.1109/ipdps.2007.370430 ◽

2007 ◽

Cited By ~ 1

Author(s):

Somasheker Akkaladevi ◽

Ajay K Katangur

Keyword(s):

Bayesian Inference ◽

Secondary Structure ◽

Structure Prediction ◽

Decision Fusion ◽

Inference Method ◽

Bayesian Inference Method

2013 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) ◽

Capturing hydrophobic moment using spectral coherence for protein secondary structure prediction

10.1109/cibcb.2013.6595403 ◽

2013 ◽

Author(s):

Pradeep Chowriappa ◽

Sumeet Dua

Keyword(s):

Secondary Structure ◽

Structure Prediction ◽

Spectral Coherence ◽

Hydrophobic Moment

A protein secondary structure prediction framework based on the Extreme Learning Machine

Neurocomputing ◽

10.1016/j.neucom.2008.01.016 ◽

2008 ◽

Vol 72 (1-3) ◽

pp. 262-268 ◽

Cited By ~ 95

Author(s):

Guoren Wang ◽

Yi Zhao ◽

Di Wang

Keyword(s):

Secondary Structure ◽

Extreme Learning Machine ◽

Structure Prediction ◽

Learning Machine

Improving protein secondary structure prediction with aligned homologous sequences

Protein Science ◽

10.1002/pro.5560050113 ◽

1996 ◽

Vol 5 (1) ◽

pp. 106-113 ◽

Cited By ~ 41

Author(s):

V. Di Francesco ◽

J. Garnier ◽

P.J. Munson

Keyword(s):

Secondary Structure ◽

Structure Prediction ◽

Homologous Sequences

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology ◽

Protein secondary structure prediction using rule induction from coverings

10.1109/cibcb.2009.4925711 ◽

2009 ◽

Author(s):

Leong Lee ◽

Jennifer L. Leopold ◽

Ronald L. Frank ◽

Anne M. Maglia

Keyword(s):

Secondary Structure ◽

Structure Prediction ◽

Rule Induction ◽

A new hybrid coding for protein secondary structure prediction based on primary structure similarity

Gene ◽

10.1016/j.gene.2017.03.011 ◽

2017 ◽

Vol 618 ◽

pp. 8-13 ◽

Cited By ~ 11

Author(s):

Zhong Li ◽

Jing Wang ◽

Shunpu Zhang ◽

Qifeng Zhang ◽

Wuming Wu

Keyword(s):

Secondary Structure ◽

Primary Structure ◽

Structure Prediction ◽

Hybrid Coding ◽

Structure Similarity