Managing and Mining Biological Graphs

Speaker:	Dr. Jiong YANG
		Electrical Engineering and Computer Science Department
		Case Western Reserve University

Title:		"Managing and Mining Biological Graphs"

Date:		Monday, 22 November 2010

Time:		4:00pm - 5:00pm

Venue:		Lecture Theater F (near lifts 25/26), HKUST

Abstract:

A large amount of biological data can be represented as graphs, e.g., gene
regulatory networks, protein interaction networks, etc. These graphs
usually consist of tens of thousands vertices and edges. This poses not
only a computational challenge, but also a biological challenge since many
of these graphs consist of a large amount of false positives and
negatives.  In this presentation, I will discuss two applications. The
first one is to find the matches of a subgraph pattern in a large
biological network with possible missing edges. To solve this problem, an
index structure with bloom filter and random spanning trees are developed,
which can achieve an efficient matching time. The second application is to
infer potential signalling transduction pathways from a protein
interaction network. The protein interaction network is first refined by
integrating other types of biological information, e.g., gene expression
profiles, protein location, etc. A trained model capturing the
characteristics of pathway interactions is learned from known signalling
pathways. Based on this model, signalling pathways are predicted. This
method can produce more accurate prediction than existing methods based on
experiments on yeast protein interaction networks.

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Biography:

Dr. Jiong Yang received his Ph.D. degree from UCLA at 1999. After
graduation, he joined IBM T. J. Watson research centers as a research
staff member. He worked as a visiting assistant professor at UIUC computer
science department in 2002. Dr. Yang joined the EECS department at Case
Western University in 2004 as the Schroeder assistant professor and now he
is an associate professor. Currently, his research is focused on managing
and analysing graph data. He has served on the program committees of
various conferences, including KDD, ICDM, SDM, ICDE. Dr. Yang is also an
associate editor of the international journal on data mining and
bioinformatics. He served as the guest editor of IEEE TKDE special issues
on Mining Biological Data and IEEE TKDD special issues on Data Mining and
Bioinformatics.   Dr. Yang has published more than eighty peer reviewed
articles in top conferences and journals. He is a senior member of IEEE.