Application of Computational Intelligence to Biology (eBook, PDF)

Redaktion: Bhramaramba, Ravi; Sekhar, Akula Chandra

• Format: PDF

Produktbeschreibung

This book is a contribution of translational and allied research to the proceedings of the International Conference on Computational Intelligence and Soft Computing. It explains how various computational intelligence techniques can be applied to investigate various biological problems. It is a good read for Research Scholars, Engineers, Medical Doctors and Bioinformatics researchers.

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 102
• Erscheinungstermin: 6. Mai 2016
• Englisch
• ISBN-13: 9789811003912
• Artikelnr.: 46969967

Autorenporträt

Dr. R. Bhramaramba is an Associate Professor in the Department of Information Technology, GITAM University. She received her PhD from JNTU Hyderabad and MS from BITS Pilani. She has published her research contributions in various reputable International Journals. Her research interests are Principal Components Analysis(PCA), Mathematical Analysis to various biological problems. Dr Akula Chandra Sekhar is a Professor & Principal in Sanketika Institute of Technology, Visakhapatnam. He was awarded PhD from Acharya Nagarjuna University for research on investigating drugs for PPAR gamma of diabetes mellitus. His research interests are QSAR studies, research on Diabetes Mellitus.

Inhaltsangabe

Enhancing the performance of Multi-parameterPatient Monitors by Homogeneous Kernel Maps.- Augmenting the performance ofMulti-patient Parameter Monitoring system.- An Efficient Classification Modelbased on Ensemble of Fuzzy-Rough Classifier for Analysis of Medical Data.- AComparative Study of Various Minutiae Extraction Methods for Fingerprint RecognitionBased on Score Level Fusion.- Hybrid Model for Analysis of Abnormalities inDiabetic Cardiomyopathy.- Computational Screening of DrugBank DataBase forNovel Cell Cycle Inhibitors.- Pathway analysis of highly conserved MitogenActivated Protein Kinases (MAPKs).- Identification of drug targets fromintegrated database of diabetes mellitus Genes using Protein-ProteinInteractions.- Distributed Data Mining for modeling and prediction of skincondiction in Cosmetic Industry - A Rough Set Theory Approach.