Learn IT - Books tags bioinformatics

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

O'Reilly, 2009

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)

MIT Press, 2001

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

Packt Publishing, 2018

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

Cambridge University Press, 2004

'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

Idea Group Publishing, 2006

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)

World Scientific Publishing, 2010

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)

John Wiley & Sons, 2007

"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

Oxford University Press, 2007

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)

MIT Press, 2004

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)

Infinity Science Press, 2006

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

MIT Press, 2001

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

World Scientific Publishing, 2007

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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