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Algorithms in Bioinformatics - Theory and Implementation (Hardcover)
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Algorithms in Bioinformatics - Theory and Implementation (Hardcover)
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ALGORITHMS IN BIOINFORMATICS Explore a comprehensive and insightful
treatment of the practical application of bioinformatic algorithms
in a variety of fields Algorithms in Bioinformatics: Theory and
Implementation delivers a fulsome treatment of some of the main
algorithms used to explain biological functions and relationships.
It introduces readers to the art of algorithms in a practical
manner which is linked with biological theory and interpretation.
The book covers many key areas of bioinformatics, including global
and local sequence alignment, forced alignment, detection of
motifs, Sequence logos, Markov chains or information entropy. Other
novel approaches are also described, such as Self-Sequence
alignment, Objective Digital Stains (ODSs) or Spectral Forecast and
the Discrete Probability Detector (DPD) algorithm. The text
incorporates graphical illustrations to highlight and emphasize the
technical details of computational algorithms found within, to
further the reader's understanding and retention of the material.
Throughout, the book is written in an accessible and practical
manner, showing how algorithms can be implemented and used in
JavaScript on Internet Browsers. The author has included more than
120 open-source implementations of the material, as well as 33
ready-to-use presentations. The book contains original material
that has been class-tested by the author and numerous cases are
examined in a biological and medical context. Readers will also
benefit from the inclusion of: A thorough introduction to
biological evolution, including the emergence of life,
classifications and some known theories and molecular mechanisms A
detailed presentation of new methods, such as Self-sequence
alignment, Objective Digital Stains and Spectral Forecast A
treatment of sequence alignment, including local sequence
alignment, global sequence alignment and forced sequence alignment
with full implementations Discussions of position-specific weight
matrices, including the count, weight, relative frequencies, and
log-likelihoods matrices A detailed presentation of the methods
related to Markov Chains as well as a description of their
implementation in Bioinformatics and adjacent fields An examination
of information and entropy, including sequence logos and
explanations related to their meaning An exploration of the current
state of bioinformatics, including what is known and what issues
are usually avoided in the field A chapter on philosophical
transactions that allows the reader a broader view of the
prediction process Native computer implementations in the context
of the field of Bioinformatics Extensive worked examples with
detailed case studies that point out the meaning of different
results Perfect for professionals and researchers in biology,
medicine, engineering, and information technology, as well as upper
level undergraduate students in these fields, Algorithms in
Bioinformatics: Theory and Implementation will also earn a place in
the libraries of software engineers who wish to understand how to
implement bioinformatic algorithms in their products.
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