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. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Darot, J., Yeang, C. H., & Haussler, D. (2006). Detecting the dependent evolution of biosequences. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3909 LNBI, pp. 595–609). https://doi.org/10.1007/11732990_48
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