The EM Algorithm and the Rise of Computational Biology
Abstract
In the past decade computational biology has grown from a cottage industry with a handful of researchers to an attractive interdisciplinary field, catching the attention and imagination of many quantitatively-minded scientists. Of interest to us is the key role played by the EM algorithm during this transformation. We survey the use of the EM algorithm in a few important computational biology problems surrounding the "central dogma"; of molecular biology: from DNA to RNA and then to proteins. Topics of this article include sequence motif discovery, protein sequence alignment, population genetics, evolutionary models and mRNA expression microarray data analysis.
Keywords
Cite
@article{arxiv.1104.2180,
title = {The EM Algorithm and the Rise of Computational Biology},
author = {Xiaodan Fan and Yuan Yuan and Jun S. Liu},
journal= {arXiv preprint arXiv:1104.2180},
year = {2011}
}
Comments
Published in at http://dx.doi.org/10.1214/09-STS312 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)