Application of Computational Intelligence to Biology

1. Auflage 2016
ISBN: 978-981-10-0390-5
Verlag: Springer Nature Singapore

Buch, Englisch, 102 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1825 g

Reihe: SpringerBriefs in Applied Sciences and Technology

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.

Zielgruppe

Research

Autoren/Hrsg.

Sekhar, Akula Chandra

Bhramaramba, Ravi

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
• Naturwissenschaften Biowissenschaften Proteinforschung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Stoffwechselstörungen
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Diabetologie

Inhaltsverzeichnis

Enhancing the performance of Multi-parameter
Patient Monitors by Homogeneous Kernel Maps.- Augmenting the performance of
Multi-patient Parameter Monitoring system.- An Efficient Classification Model
based on Ensemble of Fuzzy-Rough Classifier for Analysis of Medical Data.- A
Comparative Study of Various Minutiae Extraction Methods for Fingerprint Recognition
Based on Score Level Fusion.- Hybrid Model for Analysis of Abnormalities in
Diabetic Cardiomyopathy.- Computational Screening of DrugBank DataBase for
Novel Cell Cycle Inhibitors.- Pathway analysis of highly conserved Mitogen
Activated Protein Kinases (MAPKs).- Identification of drug targets from
integrated database of diabetes mellitus Genes using Protein-Protein
Interactions.- Distributed Data Mining for modeling and prediction of skin
condiction in Cosmetic Industry - A Rough Set Theory Approach.

Über Autor(innen)

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.