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Links to Free Computer, Mathematics, Technical Books all over the World
Bioinformatics, Computational Biology, and Healthcare IT
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  • Agent-Based Evolutionary Game Dynamics (Luis R. Izquierdo, et al.)

    A guide to implement and analyze Agent-Based Models within the framework of Evolutionary Game Theory, using NetLogo. This book will help you learn new and exciting ways of understanding evolutionary systems.

  • Biologically Inspired Robotics (Yunhui Liu, et al.)

    This book takes readers through an exploration of biologically inspired robot design and control, micro/nano bio-robotic systems, biological measurement and actuation, and applications of robotics technology to biological problems.

  • Applied Bioinformatics (David A. Hendrix)

    This book is designed to introduce students with little to no programming experience to the concepts and methodologies of bioinformatics, and contemporary software applications. It will deal with the analysis of nucleic acid sequence data.

  • A Primer for Computational Biology (Shawn T. O'Neil)

    This textbook is for anyone who needs to learn the basics of bioinformatics - the use of computational methods to better understand biological systems. It aims to provide the skills necessary for research in a data-rich world.

  • Biopython Tutorial and Cookbook (Jeff Chang, et al)

    Biopython is a set of freely available tools for biological computation written in Python. This book provides information to get you started with Biopython, in addition to specific documentation on a number of modules.

  • 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.

  • 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 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.

  • The Biostar Handbook (Dr. Istvan Albert)

    This practical book introduces readers to bioinformatics, the scientific discipline at the intersection of biology, computer science, and statistical data analytics dedicated to the digital processing of genomic information.

  • Biomedical Signal and Image Processing (Kayvan Najarian, et al.)

    It describes fundamental signal and image processing techniques that are used to process biomedical information, discusses applications of techniques in the processing of main biomedical signals and images, such as EEG, ECG, MRI, and CT.

  • 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.

  • 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. It has twelve chapters related to medical research and five focused on the biological domain.

  • 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.

  • 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..

  • 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, gives insights into the creation of innovative improvements over algorithm performance.

  • Finite Element Analysis: Biomedical Apps to Industrial

    This book presents represents a numerical technique for finding approximate solutions to partial differential equations as well as integral equations, permitting the numerical analysis of complex structures based on their material properties.

  • 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.

  • Getting to Meaningful Use and Beyond (Fred Trotter, et al)

    This book is a rosetta stone for the IT implementer that will teach you to bring organizations to implement and use electronic health records. It underlies a major federal incentives program for medical offices and hospitals that pays doctors and clinicians to move to fully electronic health records.

  • 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.

  • Biomimetics: Learning from Nature Modeling (Amitava Mukherjee)

    This book takes us into the interesting world of biomimetics and describes various arenas where the technology is applied. It discloses recent advances and new ideas in promoting the mechanism and applications of biomimetics.

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