[Colloquium] Gao/MS Presentation/Feb. 23, 2007

[Margaret Jaffey]

This is an announcement of Haitao Gao's MS Presentation.

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Date:  Friday, February 23, 2007

Time:  10:00 a.m.

Place:  Ryerson 277

M.S. Candidate:  Haitao Gao

M.S. Paper Title:  Detecting Possible Non-coding RNAs in Bacteria  
Genomes
    Using Comparative Sequence Analysis and Machine Learning

Abstract:
Non-coding RNAs(ncRNAs) are RNAs that do not directly involve in protein
synthesis. They provide regulatory functions at the level of RNA in the
cell. Unlike protein coding genes, non-coding RNA gene sequences do not
have strong statistical signals, which makes the search for non- 
coding RNA
genes a challenging task. Our research first uses BLASTN screening to
identify conserved regions in the intergenic regions of a genome, then
applies the QRNA program to look for any conserved intramolecular
secondary structure. QRNA is a program which uses a hidden Markov  
approach
to locate a semi-conserved pairwise sequence alignment and detect
significant covariance between the sequences. We then apply MFOLD, a
program which performs RNA and DNA secondary structure prediction using
nearest neighbor thermodynamic rules, to retrieve the secondary  
structure
graphs for the potential ncRNA loci. From those graphs we observe  
several
features for ncRNAs. We filter the possible loci found by QRNA program
using these features and get a reduced set of predicted possible ncRNA
loci. Therefore we have a higher accuracy detection than using QRNA  
alone.
We also use a support vector machine based machine learning method to
iteratively remove the most negative loci from the whole intergenic
regions until the rest of the intergenic set holds the predicted  
noncoding
loci. The combination of the two approaches, the comparative sequence
analysis and machine learning, gives a better prediction than any one of
the two. We finally apply the above processes to other bacteria  
genomes to
find possible non-coding RNA loci for them.

Advisor:  Prof. Rick Stevens

A draft copy of Haitao Gao's MS Paper is available in Ry 161A.

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Margaret P. Jaffey                             margaret at cs.uchicago.edu
Department of Computer Science
Student Support Rep (Ry 161A)        (773) 702-6011
The University of Chicago                  http://www.cs.uchicago.edu
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