Skip to main content Accessibility help
×
  1. Home
  2. Books
  3. Algebraic Statistics for Computational Biology
  • Cited by 146
      • Show more authors
      • You may already have access via personal or institutional login
    • Select format
    • Publisher:
      Cambridge University Press
      Publication date:
      August 2010
      August 2005
      ISBN:
      9780511610684
      9780521857000
      DOI:
      https://doi.org/10.1017/CBO9780511610684
      Dimensions:
      (253 x 177 mm)
      Weight & Pages:
      1.12kg, 434 Pages
      Dimensions:
      Weight & Pages:
      • Subjects:
      Computer Science, Computational Biology and Bioinformatics, Statistical Theory and Methods, Statistics and Probability
    You may already have access via personal or institutional login
    • Selected: Digital
    Add to cart View cart Buy from Cambridge.org
    Subjects:
    Computer Science, Computational Biology and Bioinformatics, Statistical Theory and Methods, Statistics and Probability
    Information

    Book description

    The quantitative analysis of biological sequence data is based on methods from statistics coupled with efficient algorithms from computer science. Algebra provides a framework for unifying many of the seemingly disparate techniques used by computational biologists. This book, first published in 2005, offers an introduction to this mathematical framework and describes tools from computational algebra for designing new algorithms for exact, accurate results. These algorithms can be applied to biological problems such as aligning genomes, finding genes and constructing phylogenies. The first part of this book consists of four chapters on the themes of Statistics, Computation, Algebra and Biology, offering speedy, self-contained introductions to the emerging field of algebraic statistics and its applications to genomics. In the second part, the four themes are combined and developed to tackle real problems in computational genomics. As the first book in the exciting and dynamic area, it will be welcomed as a text for self-study or for advanced undergraduate and beginning graduate courses.

    Reviews

    'As the first book in this exciting and dynamic area, it will be welcomed as a text for self-study or for advanced undergraduate and beginning graduate courses.'

    Source: L'enseignement mathematique

    '… substantial, enthusiastically presented, and confidently written …'

    Source: Publication of the International Statistical Institute

    'This book is of great interest to research workers, teachers and students in applied statistics, biology, medicine and genetics.'

    Source: Zentralblatt MATH

    Refine List

    Actions for selected content:

    Select all | Deselect all
    • View selected items
    • Export citations
    • Download PDF (zip)
    • Save to Kindle
    • Save to Dropbox
    • Save to Google Drive

    Save Search

    You can save your searches here and later view and run them again in "My saved searches".

    Please provide a title, maximum of 40 characters.
    Cancel
    ×

    Contents

    Page 1 of 2

    Contents

    Page 1 of 2

    Metrics

    Altmetric attention score

    Full text views

    Total number of HTML views: 0
    Total number of PDF views: 0 *
    Loading metrics...

    Book summary page views

    Total views: 0 *
    Loading metrics...

    * Views captured on Cambridge Core between #date#. This data will be updated every 24 hours.

    Usage data cannot currently be displayed.

    Accessibility standard: Unknown

    Why this information is here

    This section outlines the accessibility features of this content - including support for screen readers, full keyboard navigation and high-contrast display options. This may not be relevant for you.

    Accessibility Information

    Accessibility compliance for the PDF of this book is currently unknown and may be updated in the future.