Statistical algorithms and software for Genomics

Thomas Anantharaman, Bud Mishra

Research output: Contribution to journalConference articlepeer-review

Abstract

A statistical search technique is applied to certain critical computational problems in mapping the human genome, employing a Bayesian model to provide the best solution accuracy as a function of the number of parameters and heuristic search techniques derived from artificial intelligence. Critical contributions towards the solution of the assembly problem for optical mapping data are made, including the first detailed optical mapping data model, an efficient statistical algorithm that implements the update rules for the model parameters iteratively using dynamic programming, and experiments which produce highly accurate maps over wide range of experimental variations.

Original languageEnglish (US)
Pages (from-to)434-437
Number of pages4
JournalProceedings - IEEE Computer Society's International Computer Software and Applications Conference
StatePublished - 1997
EventProceedings of the 1997 21st Annual International Computer Software & Applications Conference, COMPSAC'97 - Washington, DC, USA
Duration: Aug 13 1997Aug 15 1997

ASJC Scopus subject areas

  • Software
  • Computer Science Applications

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