Phang C. Tai
According to our database1,
Phang C. Tai
authored at least 26 papers
between 2004 and 2011.
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Bibliography
2011
Understandable learning machine system design for Transmembrane or Embedded Membrane segments prediction.
Int. J. Data Min. Bioinform., 2011
2009
Novel efficient granular computing models for protein sequence motifs and structure information discovery.
Int. J. Comput. Biol. Drug Des., 2009
Tri-Cluster-Tri-Scheme-Training: Exploiting Unlabeled Data for Transmembrane Segments Prediction.
Proceedings of the Ninth IEEE International Conference on Bioinformatics and Bioengineering, 2009
2008
Proceedings of the Rule Extraction from Support Vector Machines, 2008
Efficient Super Granular SVM Feature Elimination (Super GSVM-FE) model for protein sequence motif information extraction.
Int. J. Funct. Informatics Pers. Medicine, 2008
2007
Parallel protein secondary structure prediction schemes using Pthread and OpenMP over hyper-threading technology.
J. Supercomput., 2007
Expert Syst. Appl., 2007
Understanding the Prediction of Transmembrane Proteins by Support Vector Machine using Association Rule Mining.
Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2007
Super Granular SVM Feature Elimination (Super GSVM-FE) Model for Protein Sequence Motif Informnation Extraction.
Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2007
Super Granular Shrink-SVM Feature Elimination (Super GS-SVM-FE) Model for Protein Sequence Motif Information Extraction.
Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, 2007
2006
Transmembrane segments prediction and understanding using support vector machine and decision tree.
Expert Syst. Appl., 2006
Clustering Support Vector Machines and Its Application to Local Protein Tertiary Structure Prediction.
Proceedings of the Computational Science, 2006
Novel Clustering Algorithm Combined With DSSP Post Processing For Protein Sequence Motif Discovering.
Proceedings of the 2006 IEEE International Conference on Granular Computing, 2006
A New Seed Selection Algorithm that Maximizes Local Structural Similarity in Proteins.
Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006
FIK Model: Novel Efficient Granular Computing Model for Protein Sequence Motifs and Structure Information Discovery.
Proceedings of the Sixth IEEE International Symposium on BioInformatics and BioEngineering (BIBE 2006), 2006
2005
Proceedings of the Parallel and Distributed Processing and Applications, 2005
Proceedings of the Fourth International IEEE Computer Society Computational Systems Bioinformatics Conference Workshops & Poster Abstracts, 2005
Protein Secondary Structure Prediction Using Support Vector Machine With a PSSM Profile and an Advanced Tertiary Classifier.
Proceedings of the Fourth International IEEE Computer Society Computational Systems Bioinformatics Conference Workshops & Poster Abstracts, 2005
Proceedings of the Fourth International IEEE Computer Society Computational Systems Bioinformatics Conference Workshops & Poster Abstracts, 2005
Novel Hybrid Hierarchical-K-means Clustering Method (H-K-means) for Microarray Analysis.
Proceedings of the Fourth International IEEE Computer Society Computational Systems Bioinformatics Conference Workshops & Poster Abstracts, 2005
Discovery of Local protein sequence motifs using Improved k-means Clustering Technique.
Proceedings of the Advances in Bioinformatics and Its Applications, 2005
2004
Protein secondary structure prediction using different encoding schemes and neural network architectures.
Proceedings of the Data Mining and Knowledge Discovery: Theory, 2004
Protein secondary structure prediction using support vector machine with advanced encoding schemes.
Proceedings of the Data Mining and Knowledge Discovery: Theory, 2004
Proceedings of the Data Mining and Knowledge Discovery: Theory, 2004
Factoring tertiary classification into binary classification improves neural network for protein secondary structure prediction.
Proceedings of the 2004 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2004
Transmembrane segments prediction with support vector machine based on high performance encoding schemes.
Proceedings of the 2004 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2004