# User:Jarle Pahr/Algorithms

(Difference between revisions)
 Revision as of 18:34, 8 April 2013 (view source)← Previous diff Current revision (13:40, 2 October 2013) (view source) (15 intermediate revisions not shown.) Line 8: Line 8: https://www.coursera.org/course/bioinformatics https://www.coursera.org/course/bioinformatics + + http://bioinformaticsonline.com/pages/view/920/bioinformatics-algorithms + + WABI 2013: http://algo2013.inria.fr/wabi.shtml =Concepts and categories= =Concepts and categories= + + Big O notation: http://rob-bell.net/2009/06/a-beginners-guide-to-big-o-notation/ ==Dynamic programming== ==Dynamic programming== Line 24: Line 30: =Algorithms= =Algorithms= + + Identifying K-mer clumps: + + + ==Numerical optimization== Simplex algorithm: Simplex algorithm: + + + + ==Sequence alignment== Line 45: Line 60: See also http://seqanswers.com/forums/showthread.php?t=25305 for a discussion on implementing SW. See also http://seqanswers.com/forums/showthread.php?t=25305 for a discussion on implementing SW. + + + ==Other== Burrows-Wheeler transform: Burrows-Wheeler transform: Line 65: Line 83: L. E. Baum, T. Petrie, G. Soules, and N. Weiss, "A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains", Ann. Math. Statist., vol. 41, no. 1, pp. 164–171, 1970. L. E. Baum, T. Petrie, G. Soules, and N. Weiss, "A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains", Ann. Math. Statist., vol. 41, no. 1, pp. 164–171, 1970. + + ==Mathematics== + + Fast Fourier Transform:  http://en.wikipedia.org/wiki/Fast_Fourier_transform Misc: Misc: http://www.cse.sc.edu/~maxal/csce590b/Lect01-02.pdf http://www.cse.sc.edu/~maxal/csce590b/Lect01-02.pdf + + + http://en.wikipedia.org/wiki/Kahan_summation_algorithm + '''Books/bibliography:''' '''Books/bibliography:''' Line 74: Line 100: http://www.amazon.com/Bioinformatics-Algorithms-Techniques-Applications-Wiley/dp/0470097736 http://www.amazon.com/Bioinformatics-Algorithms-Techniques-Applications-Wiley/dp/0470097736 + An introduction to bioinformatics algorithms: http://bix.ucsd.edu/bioalgorithms/ http://bioinf.me/sites/default/files/share/An%20Introduction%20to%20Bioinformatics%20Algorithms%20-%20Jones,%20Pevzner.pdf http://bioinf.me/sites/default/files/share/An%20Introduction%20to%20Bioinformatics%20Algorithms%20-%20Jones,%20Pevzner.pdf + + =Commentary and reviews= + + http://ivory.idyll.org/blog/2013-pycon-awesome-big-data-algorithms-talk.html + + http://www.nature.com/nrg/journal/v14/n5/full/nrg3433.html + + + =Natural algorithms= + + http://egtheory.wordpress.com/2013/05/29/cells-and-dna/ + + http://egtheory.wordpress.com/2013/05/19/natural-algorithms-and-the-sciences/ + + =Genetic algorithms= + + http://www.talkorigins.org/faqs/genalg/genalg.html#examples + + =Chess= + + http://www.theregister.co.uk/2012/06/26/kasparov_v_turing/ + + http://stackoverflow.com/questions/297577/is-there-a-perfect-algorithm-for-chess + + http://en.wikipedia.org/wiki/Computer_chess + + http://stackoverflow.com/questions/2026262/currently-known-best-algorithms-for-computer-chess + + http://cs.stackexchange.com/questions/7313/can-there-be-a-perfect-chess-algorithm + + http://cstheory.stackexchange.com/questions/6563/what-is-the-computational-complexity-of-solving-chess + + http://archive.computerhistory.org/projects/chess/related_materials/text/2-0%20and%202-1.Programming_a_computer_for_playing_chess.shannon/2-0%20and%202-1.Programming_a_computer_for_playing_chess.shannon.062303002.pdf + + http://archive.computerhistory.org/projects/chess/related_materials/text/2-0%20and%202-1.Programming_a_computer_for_playing_chess.shannon/2-0%20and%202-1.Programming_a_computer_for_playing_chess.shannon.062303002.pdf + + http://www.frayn.net/beowulf/theory.html + + http://www.uio.no/studier/emner/matnat/ifi/INF4130/h12/undervisningsmateriale/chess-algorithms-theory-and-practice-ver2012.pdf + + http://en.wikibooks.org/wiki/Chess_Opening_Theory + + http://en.wikibooks.org/wiki/Chess_Strategy/The_center + + http://en.wikibooks.org/wiki/Chess/Basic_Openings + + =Journals= + + http://www.mdpi.com/journal/algorithms + + =Bibliography= + + Algorithms in bioinformatics: + http://www.springer.com/computer/bioinformatics/book/978-3-642-40452-8

## Current revision

Notes on algorithms with use in bioinformatics and computational biology:

WABI 2013: http://algo2013.inria.fr/wabi.shtml

# Concepts and categories

## Dynamic programming

Examples of dynamic programming algorithms:

• Needleman-Wunschm algorithm
• Smith-Waterman algorithm
• Sankoff algorithm
• Viterbi algorithm

# Algorithms

Identifying K-mer clumps:

## Numerical optimization

Simplex algorithm:

## Sequence alignment

Needleman–Wunsch algorithm:

Dynamic programming algorithm to perform global sequence alignment. Also referred to as the "optimal matching algorithm". Introduced in 1970.

In general parlance, a Needleman-Wunsch type algorithm refers to a global alignment algorithm that takes quadratic time for a linear or affine gap penalty.

Smith Waterman algorithm:

Dynamic programming algorithm for local sequence alignment. Introduced in 1981. Can be considered a variation of the Needleman-Wunsch algorithm. Guaranteed to find the optimal local alignment with respect to the scoring system used.

## Other

Burrows-Wheeler transform:

Also called "block-sorting compression". String transformation algorithm used in data compression. Transforms a character string by permuting the order of the character, to increase the number of character repeats.

Used by the sequence alignment program BWA.

Viterbi algorithm:

From Wikipedia: "The Viterbi algorithm is a dynamic programming algorithm for finding the most likely sequence of hidden states – called the Viterbi path – that results in a sequence of observed events, especially in the context of Markov information sources and hidden Markov models."

Baum-Welch algorithm (Baum-Welch expectation maximization):

Invented by Leonard E. Baum and Lloyd R. Welch, the Baum-Welch algorithm is used to estimate the unknown parameters of a Hidden Markov Model (HMM).

L. E. Baum, T. Petrie, G. Soules, and N. Weiss, "A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains", Ann. Math. Statist., vol. 41, no. 1, pp. 164–171, 1970.

## Mathematics

Fast Fourier Transform: http://en.wikipedia.org/wiki/Fast_Fourier_transform

Misc:

Books/bibliography:

An introduction to bioinformatics algorithms: http://bix.ucsd.edu/bioalgorithms/

# Bibliography

Algorithms in bioinformatics: http://www.springer.com/computer/bioinformatics/book/978-3-642-40452-8