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Springer Handbook of Bio-/Neuroinformatics

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Cover of 'Springer Handbook of Bio-/Neuroinformatics'

Table of Contents

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    Book Overview
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    Chapter 1 Understanding Nature Through the Symbiosis of Information Science, Bioinformatics, and Neuroinformatics
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    Chapter 2 Information Processing at the Cellular Level: Beyond the Dogma
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    Chapter 3 Dielectrophoresis: Integrated Approaches for Understanding the Cell
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    Chapter 4 Information Processing at the Genomics Level
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    Chapter 5 Understanding Information Processes at the Proteomics Level
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    Chapter 6 Pattern Formation and Animal Morphogenesis
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    Chapter 7 Understanding Evolving Bacterial Colonies
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    Chapter 8 Exploring the Interactions and Structural Organization of Genomes
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    Chapter 9 Detecting MicroRNA Signatures Using Gene Expression Analysis
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    Chapter 10 Bioinformatic Methods to Discover Cis-regulatory Elements in mRNAs
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    Chapter 11 Protein Modeling and Structural Prediction
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    Chapter 12 Machine Learning Methodology in Bioinformatics
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    Chapter 13 Case-Based Reasoning for Biomedical Informatics and Medicine
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    Chapter 14 Analysis of Multiple DNA Microarray Datasets
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    Chapter 15 Fuzzy Logic and Rule-Based Methods in Bioinformatics
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    Chapter 16 Phylogenetic Cladograms: Tools for Analyzing Biomedical Data
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    Chapter 17 Protein Folding Recognition
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    Chapter 18 Kernel Methods and Applications in Bioinformatics
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    Chapter 19 Path Finding in Biological Networks
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    Chapter 20 Inferring Transcription Networks from Data
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    Chapter 21 Computational Methods for Analysis of Transcriptional Regulation
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    Chapter 22 Inferring Genetic Networks with a Recurrent Neural Network Model Using Differential Evolution
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    Chapter 23 Structural Pattern Discovery in Protein–Protein Interaction Networks
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    Chapter 24 Molecular Networks – Representation and Analysis
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    Chapter 25 Whole-Exome Sequencing Data – Identifying Somatic Mutations
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    Chapter 26 Biological Databases
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    Chapter 27 Ontologies for Bioinformatics
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    Chapter 28 Statistical Signal Processing for Cancer Stem Cell Formation
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    Chapter 29 Epigenetics
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    Chapter 30 Dynamics of Autoimmune Diseases
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    Chapter 31 Nutrigenomics
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    Chapter 32 Bioinformatics and Nanotechnologies: Nanomedicine
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    Chapter 33 Personalized Information Modeling for Personalized Medicine
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    Chapter 34 Health Informatics
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    Chapter 35 Ecological Informatics for the Prediction and Management of Invasive Species
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    Chapter 36 Information Processing in Synapses
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    Chapter 37 Computational Modeling with Spiking Neural Networks
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    Chapter 38 Statistical Methods for fMRI Activation and Effective Connectivity Studies
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    Chapter 39 Neural Circuit Models and Neuropathological Oscillations
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    Chapter 40 Understanding the Brain via fMRI Classification
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    Chapter 41 Nonlinear Adaptive Filtering in Kernel Spaces
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    Chapter 42 Recurrence Plots and the Analysis of Multiple Spike Trains
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    Chapter 43 Adaptive Multiscale Time-Frequency Analysis
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    Chapter 44 Modeling Vision with the Neocognitron
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    Chapter 45 Information Processing in the Gustatory System
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    Chapter 46 EEG Signal Processing for Brain–Computer Interfaces
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    Chapter 47 Brain-like Information Processing for Spatio-Temporal Pattern Recognition
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    Chapter 48 Neurocomputational Models of Natural Language
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    Chapter 49 Ontologies and Machine Learning Systems
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    Chapter 50 Integration of Large-Scale Neuroinformatics – The INCF
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    Chapter 51 Alzheimerʼs Disease
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    Chapter 52 Integrating Data for Modeling Biological Complexity
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    Chapter 53 A Machine Learning Pipeline for Identification of Discriminant Pathways
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    Chapter 54 Computational Neurogenetic Modeling: Gene-Dependent Dynamics of Cortex and Idiopathic Epilepsy
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    Chapter 55 Information Methods for Predicting Risk and Outcome of Stroke
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    Chapter 56 sEMG Analysis for Recognition of Rehabilitation Actions
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    Chapter 57 Brain-Like Robotics
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    Chapter 58 Developmental Learning for User Activities
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    Chapter 59 Quantum and Biocomputing – Common Notions and Targets
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    Chapter 60 Brain, Gene, and Quantum Inspired Computational Intelligence
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    Chapter 61 The Brain and Creativity
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    Chapter 62 The Allen Brain Atlas
Overall attention for this book and its chapters
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Mentioned by

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4 tweeters
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2 Facebook pages
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1 Google+ user
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1 video uploader

Citations

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Readers on

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Title
Springer Handbook of Bio-/Neuroinformatics
Published by
Springer Berlin Heidelberg, January 2014
DOI 10.1007/978-3-642-30574-0
ISBNs
978-3-64-230573-3, 978-3-64-230574-0, 978-3-64-230575-7
Authors

Nikola Kasabov

Editors

Nikola Kasabov

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 2%
Spain 1 <1%
Iran, Islamic Republic of 1 <1%
United States 1 <1%
Luxembourg 1 <1%
Unknown 114 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 23%
Student > Master 22 18%
Researcher 21 18%
Student > Bachelor 14 12%
Student > Doctoral Student 6 5%
Other 13 11%
Unknown 17 14%
Readers by discipline Count As %
Computer Science 24 20%
Agricultural and Biological Sciences 20 17%
Engineering 19 16%
Biochemistry, Genetics and Molecular Biology 10 8%
Neuroscience 5 4%
Other 22 18%
Unknown 20 17%