March 28, 2007
InterSchool Lab, 7th Floor CEPSR
Speaker: Byung-Jun Yoon, Caltech University
Hidden Markov models (HMMs) have been widely used in biological sequence analysis. Well-known applications include the identification of protein-coding genes and the alignment of DNA or protein sequences. In this talk, we present a new statistical model called context-sensitive HMM (csHMM) and consider its application in RNA sequence analysis. Noncoding RNAs (ncRNAs), which are RNAs that function without being translated intro proteins, typically have well-conserved secondary structures that are observed across different species. These structures give rise to symbol correlations between distant bases that are intertwined in a complicated manner. As traditional HMMs cannot represent such correlations, we need more complex models for the representation and analysis of RNAs. csHMMs are an extension of traditional HMMs, where certain states have variable emission and transition probabilities that depend on the “context”. This context-dependent property enables csHMMs to describe long-range correlations between distant symbols, hence making it suitable for modeling RNAs with conserved secondary structures including pseudoknots. In this talk, we first introduce the concept of csHMMs and also describe efficient algorithms that can be used with the proposed model. Second, we show how csHMMs can be utilized in RNA sequence analysis, e.g., for finding structural alignment of RNAs and performing RNA similarity search.
Byung-Jun Yoon received the B.S.E. (summa cum laude) degree in electrical engineering from Seoul National University, Seoul, Korea, in 1998, and the M.S. and Ph.D. degrees in electrical engineering from California Institute of Technology (Caltech), Pasadena, CA, in 2002 and 2006, respectively. He is currently a Postdoctoral Researcher at Caltech. His research interests include genomic signal processing, bioinformatics, and systems biology. He received the Killgore Fellowship in 2001 from Caltech and received the 2004-2005 Microsoft Research Graduate Research Fellowship. In 2003, he was awarded a prize in the student paper contest in the 37th Asilomar Conference on Signals, Systems, and Computers.