Mastering Perl for Bioinformatics [Electronic resources] نسخه متنی

2.9 Resources

I recommend the following O'Reilly sources for more
details on data structures in Perl:

Programming Perl, by Larry Wall, Tom
Christiansen, and Jon Orwant. This is the bible of Perl programming.
Everything about data structures is explained in detail.

Advanced Perl Programming by Sriram Srinivasan.
An excellent book that covers references and data structures.

Mastering Algorithms with Perl by Jon Orwant,
Jarkko Hietaniemi, and John Macdonald. A marvelous book, especially
if you like this chapter. Many interesting data structures and
algorithms are explained and implemented in Perl.

The Perl Cookbook by Tom Christiansen and Nathan
Torkington. As the title implies, this book is composed of fairly
short recipes that accomplish particular tasks, grouped according to
application area.

Here's where to go for Perl documentation:

The perlreftut tutorial page from the Perl
documentation gives a short introduction to Perl references (type
perldoc perlreftut at your
command line if Perl is installed, or visit the web page http://www.perldoc.com).

The perlref tutorial page from the Perl
documentation discusses Perl references in detail.

The perldata tutorial page from the Perl
documentation gives an introduction to Perl data structures.

The perldsc tutorial page from the Perl
documentation presents a "cookbook"
overview of Perl data structures.

The perllol tutorial page from the Perl
documentation gives an introduction to arrays of arrays.

The literature on
algorithms
is vast, including many textbooks as well as advanced monographs and
peer reviewed journals. I recommend the following sources as a few
entry points for more details on dynamic programming and algorithms:

Computer Algorithms by Sara Baase and Allen
VanGelder (Addison Wesley). This book is clearly written for the
undergraduate level, and includes a very nice explanation of the
algorithm presented in this chapter.

Introduction to Algorithms by Thomas Cormen,
Charles Leiserson, and Ron Rivest (MIT Press and McGraw-Hill). An
excellent and standard college textbook, well written; can serve as a
reference book for the serious programmer.

Algorithms on Strings, Trees, and Sequences: Computer
Science and Computational Biology by Dan Gusfield
(Cambridge University Press). This book specializes in algorithms for
strings, including such topics as sequence alignment.
It's very detailed, but even so, not
completethis is a big field! The best single source on string
algorithms, with lots of information about biological sequence
similarity.

Data Structures and Algorithms by Alfred Aho,
John E. Hopcroft, and Jeffrey Ullman (Addison Wesley). This is the
classic book on the science of algorithms.

Introduction to Parallel Algorithms and Architectures:
Arrays, Trees, Hypercubes by Frank Thomson Leighton
(Morgan Kaufmann). A comprehensive, rigorous text and reference book.

Randomized Algorithms by Rajeev Motwani and
Prabhakar Raghavan (Cambridge University Press). A clear, rigorous
course.