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Bioinformatics Programming Using Python: Practical Programming for Biological Data (Animal Guide)
Bioinformatics Programming Using Python: Practical Programming for Biological Data (Animal Guide)

Powerful, flexible, and easy to use, Python is an ideal language for building software tools and applications for life science research and development. This unique book shows you how to program with Python, using code examples taken directly from bioinformatics. In a short time, you'll be using sophisticated techniques and...

Bioinformatics: The Machine Learning Approach, Second Edition (Adaptive Computation and Machine Learning)
Bioinformatics: The Machine Learning Approach, Second Edition (Adaptive Computation and Machine Learning)

We have been very pleased, beyond our expectations, with the reception of the first edition of this book. Bioinformatics, however, continues to evolve very rapidly, hence the need for a new edition. In the past three years, fullgenome sequencing has blossomed with the completion of the sequence of the fly and the first draft of the...

Bioinformatics with Python Cookbook: Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology, 2nd Edition
Bioinformatics with Python Cookbook: Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology, 2nd Edition

Discover modern, next-generation sequencing libraries from Python ecosystem to analyze large amounts of biological data

Key Features

  • Perform complex bioinformatics analysis using the most important Python libraries and applications
  • Implement next-generation sequencing,...
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
'Kernel methods form an important aspect of modern pattern analysis, and this book gives a lively and timely account of such methods. ... if you want to get a good idea of the current research in this field, this book cannot be ignored.' SIAM Review '... the book provides an excellent overview of this growing field. I highly recommend it to those...
Neural Networks in Healthcare: Potential and Challenges
Neural Networks in Healthcare: Potential and Challenges
Healthcare costs around the globe are on the rise, creating a strong need for new ways of assisting the requirements of the healthcare system. Besides applications in other areas, neural networks have naturally found many promising applications in the health and medicine areas. Neural Networks in Healthcare: Potential and Challenges presents...
Machine Learning Approaches to Bioinformatics (Science, Engineering, and Biology Informatics)
Machine Learning Approaches to Bioinformatics (Science, Engineering, and Biology Informatics)

This book covers a wide range of subjects in applying machine learning approaches for bioinformatics projects. The book succeeds on two key unique features. First, it introduces the most widely used machine learning approaches in bioinformatics and discusses, with evaluations from real case studies, how they are used in individual...

A Statistical Approach to Neural Networks for Pattern Recognition (Wiley Series in Computational Statistics)
A Statistical Approach to Neural Networks for Pattern Recognition (Wiley Series in Computational Statistics)
"The book provides an excellent introduction to neutral networks from a statistical perspective." (International Statistical Review, 2008)

"Successful connects logistic regression and linear discriminant analysis, thus making it critical reference and self-study guide for students and professionals alike in the...

Reconstructing Evolution: New Mathematical and Computational Advances
Reconstructing Evolution: New Mathematical and Computational Advances
Evolution is a complex process, acting at multiple scales, from DNA sequences and proteins to populations of species. Understanding and reconstructing evolution is of major importance in numerous subfields of biology. For example, phylogenetics and sequence evolution is central to comparative genomics, attempts to decipher genomes, and molecular...
Introduction to Machine Learning (Adaptive Computation and Machine Learning)
Introduction to Machine Learning (Adaptive Computation and Machine Learning)
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, recognize faces or spoken speech, optimize robot behavior so that a task can be completed...
Digital Signal Processing Using MATLAB and Wavelets (Electrical Engineering)
Digital Signal Processing Using MATLAB and Wavelets (Electrical Engineering)
Although DSP has long been considered an EE topic, recent developments have also generated significant interest from the computer science community. DSP applications in the consumer market, such as bioinformatics, the MP3 audio format, and MPEG-based cable/satellite television have fueled a desire to understand this technology outside of hardware...
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels--for a number of learning tasks. Kernel machines provide a modular framework...
Neural Networks and Computing: Learning Algorithms and Applications
Neural Networks and Computing: Learning Algorithms and Applications

The area of Neural computing that we shall discuss in this book represents a combination of techniques of classical optimization, statistics, and information theory. Neural network was once widely called artificial neural networks, which represented how the emerging technology was related to artificial intelligence. It once was a topic that...

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