All Shops

Go to British Wildlife

6 issues per year 84 pages per issue Subscription only

British Wildlife is the leading natural history magazine in the UK, providing essential reading for both enthusiast and professional naturalists and wildlife conservationists. Published six times a year, British Wildlife bridges the gap between popular writing and scientific literature through a combination of long-form articles, regular columns and reports, book reviews and letters.

Subscriptions from £25 per year

Conservation Land Management

4 issues per year 44 pages per issue Subscription only

Conservation Land Management (CLM) is a quarterly magazine that is widely regarded as essential reading for all who are involved in land management for nature conservation, across the British Isles. CLM includes long-form articles, events listings, publication reviews, new product information and updates, reports of conferences and letters.

Subscriptions from £18 per year
Academic & Professional Books  Reference  Data Analysis & Modelling  Data Analysis & Statistics

Bioinformatics: The Machine Learning Approach

By: Pierre Baldi and Soren Brunak
351 pages, 11 col plates, figs
Publisher: MIT Press
Bioinformatics: The Machine Learning Approach
Click to have a closer look
Select version
  • Bioinformatics: The Machine Learning Approach ISBN: 9780262025065 Edition: 2 Hardback Aug 2001 Usually dispatched within 4 days
    £53.99
    #124295
Selected version: £53.99
About this book Customer reviews Biography Related titles

About this book

An unprecedented wealth of data is being generated by genome sequencing projects and other experimental efforts to determine the structure and function of biological molecules. The demands and opportunities for interpreting these data are expanding rapidly. Bioinformatics is the development and application of computer methods for management, analysis, interpretation, and prediction, as well as for the design of experiments. Machine learning approaches (e.g., neural networks, hidden Markov models, and belief networks) are ideally suited for areas where there is a lot of data but little theory, which is the situation in molecular biology. The goal in machine learning is to extract useful information from a body of data by building good probabilistic models - and to automate the process as much as possible. In this book Pierre Baldi and Soren Brunak present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed both at biologists and biochemists who need to understand new data-driven algorithms and at those with a primary background in physics, mathematics, statistics, or computer science who need to know more about applications in molecular biology. This edition contains expanded coverage of probabilistic graphical models and of the applications of neural networks, as well as a new chapter on microarrays and gene expression. The entire text has been extensively revised.

Customer Reviews

Biography

Pierre Baldi is Professor of Information and Computer Science and of Biological Chemistry (College of Medicine) and Director of the Institute for Genomics and Bioinformatics at the University of California, Irvine. Soren Brunak is Professor and Director of the Center for Biological Sequence Analysis at the Technical University of Denmark.

By: Pierre Baldi and Soren Brunak
351 pages, 11 col plates, figs
Publisher: MIT Press
Media reviews

This is a very good book, written with a high level of erudition and insight. Gustavo A. Stolovitzky Physics Today

Current promotions
Best of Winter 2018Handbook of the Bees of the British Isles (2-Volume Set)Order your free copy of our 2018 equipment catalogueBritish Wildlife