Detecting the Dependent Evolution of Biosequences

Abstract. A probabilistic graphical model is developed in order to detect the dependent evolution between different sites in biological sequences. Given a multiple sequence alignment for each molecule of interest and a phylogenetic tree, the model can predict potential interactions within or between nucleic acids and proteins. Initial validation of the model is carried out using tRNA sequence data. The model is able to accurately identify the secondary structure of tRNA as well as several known tertiary interactions.

• Type: Conference
• Year: 2006
• Where: RECOMB
• Authors: Jeremy Darot, Chen-Hsiang Yeang, David Haussler
• Keywords: Computational Biology, Multiple Sequence Alignment, Probabilistic Graphical Model, RECOMB 2006, TRNA Sequence Data