Skip Search and Navigation

University of Louisville Bioinformatics

Bioinformatics Research at the University of Louisville


Project:

DNA Motif Detection Using Particle Swarm Optimization and Expectation-Maximization


Authors:

C. Timothy Hardin(1,2,3) Eric C. Rouchka(1,2)

  1. University of Louisville Department of Computer Engineering and Computer Science.
  2. University of Louisville Bioinformatics Research Group.
  3. University of Louisville Department of Industrial Engineering.
Motivation:
Motif discovery, the process of discovering a meaningful pattern of nucleotides or amino acids that is shared by two or more molecules, is an important part of the study of gene function. In this work, we developed a hybrid motif discovery approach based upon a combination of Particle Swarm Optimization (PSO) and the Expectation-Maximization (EM) algorithm. In the proposed algorithm, we use PSO to generate a seed for the EM algorithm.

 
Results:
The Motif Swarm Algorithm is available as a C# interface for windows users.

LATEST VERSION

  • C# Graphical User Interface SeqAlign.exe

    (Requires Microsoft's .NET Framework Version 2.0 Redistribution Package (x86) available from microsoft.com)

PRIOR VERSION SOURCE CODE

Citations:
Hardin CT, Rouchka EC (2005). DNA Motif Detection Using Particle Swarm Optimization and Expectation-Maximization. Proc IEEE Swarm Intell Symp., 2005:181-184. (PMCID: 137489, PMID: 20436786)


Top of Page