Produktbild: Springer Handbook of Bio-/Neuro-Informatics

Springer Handbook of Bio-/Neuro-Informatics

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

18.11.2013

Abbildungen

500 farbige Abbildungen, 70 farbige Tabellen

Herausgeber

Nikola Kasabov

Verlag

Springer Berlin

Seitenzahl

1229

Maße (L/B/H)

24.9/20/5.8 cm

Gewicht

2506 g

Auflage

2014

Sprache

Englisch

ISBN

978-3-642-30573-3

Beschreibung

Rezension

From the book reviews:

“This handbook is structured in 12 parts, covering a wide variety of notions associated with bio- and neuroinformatics … . The handbook is a valuable and timely resource, which can be used by undergraduates, postgraduates and established researchers. By presenting together a variety of (linked) approaches, it provides a fantastic source for bioinformaticians and neuroinformaticians alike.” (Irina Ioana Mohorianu, zbMATH, Vol. 1304, 2015)

“This is the very best of the encyclopedias and comprehensive book’s about both Medical, Molecular, Genetic, and Neural Informatics currently available. … this is a good textbook for graduate students as a Primer on Neurophysiology and Molecular Medicine. Professionals in these areas will find this book very useful in their daily work … . book is very well referenced at the end of each chapter discussion. … I am pleased to recommend this book to new researchers in the field.” (Joseph J. Grenier, Amazon.com, November,2014)

Portrait

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 titleof ‘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) 

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

18.11.2013

Abbildungen

500 farbige Abbildungen, 70 farbige Tabellen

Herausgeber

Nikola Kasabov

Verlag

Springer Berlin

Seitenzahl

1229

Maße (L/B/H)

24.9/20/5.8 cm

Gewicht

2506 g

Auflage

2014

Sprache

Englisch

ISBN

978-3-642-30573-3

Herstelleradresse

Springer Nature Customer Service Center GmbH
Europaplatz 3
69115 Heidelberg
DE
ProductSafety@springernature.com

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  • Produktbild: Springer Handbook of Bio-/Neuro-Informatics
  • 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