Springer Handbook of Bio-/Neuro-Informatics

Springer Handbook of Bio-/Neuro-Informatics

by Nikola Kasabov (Editor)


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Product Details

ISBN-13: 9783642305733
Publisher: Springer Berlin Heidelberg
Publication date: 02/04/2014
Series: Springer Handbooks
Edition description: 2014
Pages: 1229
Product dimensions: 7.60(w) x 9.53(h) x (d)

About the Author

Nikola K Kasabov is currently the Director of the Knowledge Engineering & Discovery Research Institute and Personal Chair of Knowledge Engineering in the School of Information Technology, Auckland University of Technology, New Zealand.
He has published over 350 works, among them journal papers, textbooks, edited research books and monographs, conference papers, book chapters, edited conference proceedings, patents and authorship certificates in the area of intelligent systems, connectionist and hybrid connectionist systems, fuzzy systems, expert systems, speech recognition, bioinformatics, neurocomputing and neural networks.

Prof. Kasabov is a Fellow of IEEE, Fellow of the Royal Society of New Zealand and the New Zealand Computer Society, President of the International Neural Network Society (INNS), Past President of the Asia Pacific Neural Network Assembly (APNNA) and also a member of INNS, ENNS, and the IEEE Computer Society. Recently Prof. Kasabov was endowed the title of ‘Guest Professor’ at Shanghai Jiao Tong University, China.

Prof. Kasabov is the General Chairman of a series of biannual international conferences on Neurocomputing in New Zealand. In 2007 Prof. Kasabov was awarded The Bayer Science Innovator Award. He received The Royal Society of New Zealand Silver Medal for contribution to Science and Technology in 2001. He is an Associate Editor of numerous international journals and a leader of a National Research Programme funded by the Foundation for Research, Science and Technology (FRST)

Table of Contents

Chap. 1 Understanding Nature - Symbiosis of Information Science, Bioinformatics and Neuroinformatics

Part A Understanding Information Processes in Biological Systems
(Ed. Heike Sichtig)

Chap. 2 Information Processing at the Cellular Level.- Chap. 3 Integrated Approaches for Understadning the Cell.- Chap. 4 Information Processing at the Genomics Level.- Chap. 5 Understanding Information Processes at the Proteomics Level.- Chap. 6 Pattern Formation and Animal Morphogenesis.- Chap. 7 Understanding Evolving Bacteria Colonies

Part B Molecular Biology, Genome and Proteome Informatics
(Ed.: Chris Brown)

Chap. 8 Exploring Interactions and Structural Organization of Genomes.- Chap. 9 Detecting microRNA Signatures Using Gene Expression Analysis.- Chap. 10 Bioinformatics Methods to Discover Cis-Regulatory Elements.- Chap. 11 Protein Modeling and Structural Prediction

Part C Machine-Learning Methods
(Eds: Irwin King,Kaizhu Huang, Heike Sichtig)

Chap. 12 Machine Learning Methodology in Bioinformatics.- Chap. 13 Case-Based Reasoning for Biomedical Informatics and Medicine.- Chap. 14 Analysis of Multiple DNA Microarray Datasets.- Chap. 15 Fuzzy Logic and Rule-Based Methods in Bioinformatics.- Chap. 16 Phylogenetic Cladograms: Understanding and Learning from Biomedical Data.- Chap. 17 Understanding Protein Folding Modeling.- Chap. 18 Kernel Methods and Applications in Bioinformatics

Part D Modeling Regulatory Networks: The Systems Biology Approach
(Eds: Chris Brown, Heike Sichtig, Irwin King, Kaizhu Huang, Francesco Masulli)

Chap. 19 Path Finding in Biological Networks.- Chap. 20 Inferring Transcription Networks from Data.- Chap. 21 Analysis of Transcriptional Regulation.- Chap. 22 Inferring Genetic Networks.-
Chap. 23 Structural Pattern Discovery.- Chap. 24 Molecular Networks - Representation and Analysis.- Chap. 25 Whole-Exome Sequencing Data

Part E Bioinformatics Databases and Ontologies
(Ed.: Francesco Masulli)

Chap. 26 Bioinformatics Databases.- Chap. 27 Ontologies for Bioinformatics

Part F Bioinformatics in Medicine, Health and Ecology
(Eds: Francesco Masulli, Danilo Mandic)

Chap. 28 Statistical Signal Processing Models And Methods.- Chap. 29 Epigenetics.- Chap. 30 Control of Autoimmune Diseases.- Chap. 311 Nutrigenomics.- Chap. 32 Bioinformatics and Nanotechnologies: Nanomedicine.- Chap. 33 Information Modeling Technologies for Personalized Medicine.- Chap. 34 Health Informatics.- Chap. 35 Ecological Informatics

Part G Understanding Information Processes in the Brain and the Nervous System
(Ed.: Heike Sichtig)

Chap. 36 Information Processing in Synapses.- Chap. 37 Spiking Neural Networks.- Chap. 38 Statistical Methods for fMRI Activation Detection.- Chap. 39 Neural Circuit Models and Neuropathological Oscillations.- Chap. 40 Understanding the Brain via fMRI Classification

Part H Advanced Signal-Processing Methods for Brain Signal Analysis and Modeling
(Ed.: Danilo Mandic)

Chap. 41 Nonlinear Adaptive Filtering in Kernel Spaces.- Chap. 42 Analysis of Multiple Spike Trains.- Chap. 43 Adaptive Multiscale Time-Frequency Analysis

Part I Information Modeling of Perception, Sensation and Cognition
(Eds: Lubica Benuskova, Heike Sichtig)

Chap. 44 Modeling Vision with the Neocognitron.- Chap. 45 Information Processing in the Gustatory System.- Chap. 46 EEG Signal Processing for Brain Computer Interfaces.- Chap. 47 Spiking Neural Networks.- Chap. 48 Neurocomputational Models of Natural Language

Part J Neuroinformatics Databases and Ontologies
(Eds: Shiro Usui, Raphael Ritz)

Chap. 49 Ontologies and Machine Learning Systems .- Chap. 50 Integration of Large-Scale Neuroinformatics

Part K Information Modeling for Brain Diseases
(Eds: Lubica Benuskova, Francesco Masulli)

Chap. 51 Alzheimer’s Disease.- Chap. 52 Integrating Data for Modeling Biological Complexity.- Chap. 53 A Machine Learning Pipeline .- Chap. 54 Modeling Gene-Dependent Dynamics of Cortex and Epilepsy.- Chap. 55 Information Methods for Predicting Stroke.- Chap. 56 Recognition of Rehabilitation Actions

Part L Nature Inspired Integrated Information Technologies
(Eds: Lubica Benuskova,Danilo Mandic)

Chap. 57 Brain-Like Robotics.- Chap. 58 Developmental Learning for User Activities.- Chap. 59 Quantum and Biocomputing - Common Notions and Targets.- Chap. 60 Brain-, Gene-, and Quantum-Inspired Computational Intelligence.- Chap. 61 The Brain and Creativity.- Chap. 62 The Allen Brain Atlas

Acknowledgements.- About the Authors.- Subject Index

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