SCHOOL OF COMPUTING,NUS 
 
POSTGRADUATE SEMINAR BY 
 
MS JI LIPING
 
Mining Localized Co-expressed Gene Patterns from Microarray Data


Executive Classroom, SoC-1 level 5
 
22 January 2007, 12.00pm

 
Abstract: 
With the new advances in DNA microarray technology, expression
levels of thousands of genes can be simultaneously measured
efficiently during important biological process and across
collections of related samples. Analyzing the microarray data to
identify localized co-expressed gene patterns are essential in
revealing the gene functions, gene regulations, subtypes of cells,
and cellular processes of gene regulation networks. Hence,
researchers are recently motivated to mine co-expressed gene
patterns from microarray data.

We studied both the static and dynamic aspects of
localized co-expressed gene patterns and categoried the patterns
into three types: co-attribute patterns, co-tendency patterns and
time-lagged patterns. We designed new algorithms to identify the
three types of localized co-expressed gene patterns, and conducted
experiments on both synthetic and real microarray
datasets. Our experiments show the effectiveness and efficiency of
our algorithms in mining the localized co-expressed gene patterns.