Computational Intelligence and Pattern Analysis in
Chapter 1 Computational Intelligence: Foundations, views, and up to date developments (pages 1–37): Swagatam Das, Ajith Abraham and B. ok. Panigrahi
Chapter 2 basics of development research: a short review (pages 39–58): Basabi Chakraborty
Chapter three organic Informatics: facts, instruments, and functions (pages 59–69): Kevin Byron, Miguel Cervantes?Cervantes and Jason T. L. Wang
Chapter four Promoter acceptance utilizing Neural community ways (pages 71–97): T. Sobha Rani, S. Durga Bhavani and S. Bapi Raju
Chapter five Predicting microRNA Prostate melanoma goal Genes (pages 99–115): Francesco Masulli, Stefano Rovetta and Giuseppe Russo
Chapter 6 Structural seek in RNA Motif Databases (pages 117–130): Dongrong Wen and Jason T. L. Wang
Chapter 7 Kernels on Protein buildings (pages 131–167): Sourangshu Bhattacharya, Chiranjib Bhattacharyya and Nagasuma R. Chandra
Chapter eight Characterization of Conformational styles in lively and Inactive sorts of Kinases utilizing Protein Blocks process (pages 169–187): G. Agarwal, D. C. Dinesh, N. Srinivasan and Alexandre G. de Brevern
Chapter nine Kernel functionality functions in Cheminformatics (pages 189–235): Aaron Smalter and Jun Huan
Chapter 10 In Silico Drug layout utilizing a Computational Intelligence procedure (pages 237–256): Soumi Sengupta and Sanghamitra Bandyopadhyay
Chapter eleven built-in Differential Fuzzy Clustering for research of Microarray information (pages 257–276): Indrajit Saha and Ujjwal Maulik
Chapter 12 deciding upon power Gene Markers utilizing SVM Classifier Ensemble (pages 277–291): Anirban Mukhopadhyay, Ujjwal Maulik and Sanghamitra Bandyopadhyay
Chapter thirteen Gene Microarray facts research utilizing Parallel element Symmetry?Based Clustering (pages 293–306): Ujjwal Maulik and Anasua Sarkar
Chapter 14 concepts for Prioritization of Candidate disorder Genes (pages 307–324): Jieun Jeong and Jake Y. Chen
Chapter 15 Prediction of Protein–Protein Interactions (pages 325–347): Angshuman Bagchi
Chapter sixteen examining Topological homes of Protein–Protein interplay Networks: A standpoint towards structures Biology (pages 349–368): Malay Bhattacharyya and Sanghamitra Bandyopadhyay
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Reynolds, and T. Kohler (2003), A multi-agent simulation using cultural algorithms: The effect of culture on the resilience of social systems, IEEE Congress on Evolutionary Computation December 5–12, 2003, Canberra, Australia. 36. K. S. Lee and Z. W. Geem (2005), A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice, Computer Methods in Applied Mechanics and Engineering, Vol. 194, No. 36–38, pp. 3902–3933. 37. D. ) (1999), Artificial Immune Systems and Their Applications, SpringerVerlag, Inc.
24. H. J. Zimmerman (1996), Fuzzy Set Theory and Its Applications, Kluwer Academic, Dordrecht, The Netherlands, pp. 131–162. 25. A. Abraham (2001), Neuro-Fuzzy Systems: State-of-the-Art Modeling Techniques, Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence, Lecture Notes in Computer Science. Mira J. and Prieto A. ), Vol. 2084, Springer-Verlag Germany, pp. 269–276. 26. T. Back, D. B. Fogel, and Z. ) (1997), Handbook of Evolutionary Computation, Oxford University Press.
33. E. Bonabeau, M. Dorigo, and G. Theraulaz (1999), Swarm Intelligence: From Natural to Artificial Systems, Oxford University Press Inc. P1: TIX/FYX P2: MRM c01 JWBS033-Maulik 34 July 21, 2010 9:59 Printer Name: Yet to Come COMPUTATIONAL INTELLIGENCE 34. T. M. Martinetz and K. J. Schulten (1991), A neural-gas network learns topologies, T. Kohonen, K. M¨akisara, O. Simula, and J. ), Artificial Neural Networks, North-Holland, Amsterdam, The Netherlands, pp. 397–402. 35. Z. Kobti, R. Reynolds, and T.