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The EM Algorithm and the Rise of Computational Biology

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2010

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Institute of Mathematical Statistics
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Fan, Xiaodan, Yuan Yuan, and Jun S. Liu. 2010. “The EM Algorithm and the Rise of Computational Biology.” Statistical Science 25 (4) (November): 476–491. doi:10.1214/09-sts312.

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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.

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