Application of Computational Intelligence to Biology

1. Front Matter

   Pages i-ix

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2. Enhancing the Performance of Multi-parameter Patient Monitors by Homogeneous Kernel Maps

   • S. Premanand, S. Sugunavathy

   Pages 1-7

3. Augmenting the Performance of Multi-patient Parameter Monitoring System in LKSVM

   • S. Premanand, S. Sugunavathy

   Pages 9-18

4. An Efficient Classification Model Based on Ensemble of Fuzzy-Rough Classifier for Analysis of Medical Data

   • M. Sujatha, G. Lavanya Devi, N. Naresh, K. Srinivasa Rao

   Pages 19-27

5. A Comparative Study of Various Minutiae Extraction Methods for Fingerprint Recognition Based on Score Level Fusion

   • P. Aruna Kumari, G. JayaSuma

   Pages 29-41

6. Hybrid Model for Analysis of Abnormalities in Diabetic Cardiomyopathy

   • Fahimuddin Shaik, Anil Kumar Sharma, Syed Musthak Ahmed

   Pages 43-60

7. Computational Screening of DrugBank DataBase for Novel Cell Cycle Inhibitors

   • Satyanarayana Kotha, Yesu Babu Adimulam, R. Kiran Kumar

   Pages 61-70

8. Pathway Analysis of Highly Conserved Mitogen Activated Protein Kinases (MAPKs)

   • N. Deepak, Yesu babu Adimulam, R. Kiran Kumar

   Pages 71-82

9. Identification of Drug Targets from Integrated Database of Diabetes Mellitus Genes Using Protein-Protein Interactions

   • Duggineni Kalyani, Naresh Babu Muppalaneni, Ch Ambedkar, Kiran Kumar Reddi

   Pages 83-86

10. Distributed Data Mining for Modeling and Prediction of Skin Condition in Cosmetic Industry—A Rough Set Theory Approach

    • P. M. Prasuna, Y. Ramadevi, A. Vinay Babu

    Pages 87-102

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.

• Comparative genomics
• Diabetes mellitus
• Learning based optimization
• Gene functional enrichment
• Protein-protein interaction
• Support Vector Machines
• Fuzzy-rough classifier
• diabetes
• Protein Structure

• GITAM University, Visakhapatnam, India

  Ravi Bhramaramba

• Sanketika Institute of Technology, Visakhapatnam, India

  Akula Chandra Sekhar

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.

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