Journal of Computer Science & Systems Biology

Department of Computer Science, University of Ibadan, Nigeria

Publications

• Research Article   
  Motif Discovery in DNA Sequences Using an Improved Gibbs (i Gibbs) Sampling Algorithm
  Author(s): Makolo AU and Lamidi UA*
  
  Motifs are repeated patterns of short sequences usually of varying lengths between 6 to 20 bases. Within Deoxyribonucleic Acid (DNA) sequences, these motifs constitute the conserved region of most common signatures for recognizing protein domains that are relevant in it evolution, function and interaction. The Gibbs sampling is a Markov Chain Monte Carlo (MCMC) algorithm which has been applied in the past to discover motifs in DNA sequences. A problem with this technique is the profusion of iterative operations in the sampling process because it progressively chooses new possible motif positions from a continuous randomize sampling in DNA sequences. We applied an Improved Gibbs (iGibbs) sampling algorithm on Breast Cancer (brca) human disease DNA sequences obtained from https://www.ncbi.nlm.nih.gov/nuccore to overcome this unwieldy iteration by altering the.. Read More»
  

  Abstract PDF