Scalable Pattern Recognition Algorithms - Maji, Pradipta

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Auteur(s) : Maji, Pradipta - Paul, Sushmita

Editeur : Springer International Publishing Ag

Langue : Anglais

Parution : 01/08/2016

Format : Moyen, de 350g à 1kg

Nombre de pages : 328

Expédition : 499

Dimensions : 23.5 x 15.5 x 1.8

ISBN : 3319379658

Résumé :

Introduction to Pattern Recognition and Bioinformatics.- Part I Classification.-Neural Network Tree for Identification of Splice Junction and Protein Coding Region in DNA.- Design of String Kernel to Predict Protein Functional Sites Using Kernel-Based Classifiers.- Part II Feature Selection.-Rough Sets for Selection of Molecular Descriptors to Predict Biological Activity of Molecules.- f-Information Measures for Selection of Discriminative Genes from Microarray Data.- Identification of Disease Genes Using Gene Expression and Protein-Protein Interaction Data.- Rough Sets for Insilico Identification of Differentially Expressed miRNAs.- Part III Clustering.-Grouping Functionally Similar Genes from Microarray Data Using Rough-Fuzzy Clustering.- Mutual Information Based Supervised Attribute Clustering for Microarray Sample Classification.- Possibilistic Biclustering for Discovering Value-Coherent Overlapping d -Biclusters.- Fuzzy Measures and Weighted Co-Occurrence Matrix for Segmentation of Brain MR Images.

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Biographie:
Dr. Pradipta Maji is an?Associate Professor in the Machine Intelligence Unit at the Indian Statistical Institute, Kolkata, India. Dr. Sushmita Paul is a Research Associate at the same institution....

Sommaire:

Introduction to Pattern Recognition and Bioinformatics.- Part I Classification.- Neural Network Tree for Identification of Splice Junction and Protein Coding Region in DNA.- Design of String Kernel to Predict Protein Functional Sites Using Kernel-Based Classifiers.- Part II Feature Selection.- Rough Sets for Selection of Molecular Descriptors to Predict Biological Activity of Molecules.- f -Information Measures for Selection of Discriminative Genes from Microarray Data.- Identification of Disease Genes Using Gene Expression and Protein-Protein Interaction Data.- Rough Sets for Insilico Identification of Differentially Expressed miRNAs.- Part III Clustering.- Grouping Functionally Similar Genes from Microarray Data Using Rough-Fuzzy Clustering.- Mutual Information Based Supervised Attribute Clustering for Microarray Sample Classification.- Possibilistic Biclustering for Discovering Value-Coherent Overlapping d -Biclusters.- Fuzzy Measures and Weighted Co-Occurrence Matrix for Segmentation of Brain MR Images.