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Bioinformatics, Computational Biology, and Healthcare IT
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  • Large Scale Data Handling in Biology (Karol Kozak)

    The book covers the data storage system, computational approaches to biological problems, an introduction to workflow systems, data mining, data visualization, and tips for tailoring existing data analysis software to individual research needs.

  • Data Mining in Medical and Biological Research

    This book intends to bring together the most recent advances and applications of data mining research in the promising areas of medicine and biology from around the world.

  • Data Mining Applications in Engineering and Medicine

    This book targets to help data miners who wish to apply different data mining techniques, including statistics, machine learning, data management and databases, pattern recognition, artificial intelligence, etc.

  • Data Mining and Knowledge Discovery in Real Life Applications

    This book presents four different ways of theoretical and practical advances and applications of data mining in different promising areas like Industrialist, Biological, and Social Networks..

  • Biological Signal Analysis with MATLAB (R. Palaniappan)

    This book will provide the reader with an understanding of biological signals and digital signal analysis techniques such as conditioning, filtering, classification and statistical validation for solving practical biological signal analysis problems using MATLAB.

  • Bioinformatics Data Skills (Vince Buffalo)

    This practical book teaches the skills that scientists need for turning large sequencing datasets into reproducible and robust biological findings. It demsonstrates the practice of bioinformatics through data skills.

  • Bio-Inspired Computational Algorithms and Their Applications

    Integrates contrasting techniques of genetic algorithms, artificial immune systems, particle swarm optimization, and hybrid models to solve many real-world problems.

  • Artificial Neural Networks - Biomedical Applications

    The book begins with fundamentals of artificial neural networks, which cover an introduction, design, and optimization. Advanced architectures for biomedical applications, which offer improved performance and desirable properties, follow.

  • Bioinformatics in Tropical Disease Research (Arthur Gruber, et al)

    This book is intended to serve both as a textbook for short bioinformatics courses and as a base for a self-teaching endeavor. It consists of two parts: A. Bioinformatics Techniques and B. Case Studies.

  • Computational Biology and Applied Bioinformatics

    This book presents some theoretical issues, reviews, and a variety of bioinformatics applications. For better understanding, the chapters were grouped in two parts. In Part I, the chapters are more oriented towards literature review and theoretical issues.

  • Systems and Computational Biology - Computational Modeling

    In this book, we are exploring new scientific and technological systems to benefit human health, human food and animal feed production, and environmental protections. Indeed, we are humbled by the complexity, extent and beauty of cross-talks in various biological systems

  • Bioinformatics (Horacio Perez-Sanchez)

    This book is packed with valuable information that introduces you to this exciting Bioinformatics, divided into different research areas relevant in Bioinformatics such as biological networks, next generation sequencing, high performance computing, molecular modeling, structural bioinformatics, molecular modeling and intelligent data analysis.

  • Bioinformatics - Trends and Methodologies (Mahmood A. Mahdavi)

    A collection of different views on most recent topics and basic concepts in bioinformatics which suits young researchers who seek basic fundamentals of bioinformatic skills such as data mining, data integration, sequence analysis and gene expression analysis.

  • Introduction to Programming for Medical Image Analysis with VTK

    Provide sufficient introductory material for engineering graduate students with background in programming in C and C++ to acquire the skills to leverage modern open source toolkits in medical image analysis and visualization.

  • Unix and Perl Primer for Biologists (Keith Bradnam, et al)

    This is a basic introductory course for biologists to learn the essential aspects of the Perl programming language. It is aimed at people with no prior experience in either programming or Unix.

  • Bioinformatics, Computational Biology, and Healthcare IT

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