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III-CXT: Collaborative Research: A High-Throughput Approach to the Assignment of Orthologous Genes Based on Genome Rearrangement

News on the project will be posted periodically.

Introduction: Orthologous genes, or orthologs, are genes in different species that have evolved directly from a common ancestral gene. Genome-scale assignment of orthologs is a fundamental and challenging problem in computational biology, and has a wide range of applications in comparative genomics and functional genomics. This project continues the development of the parsimony approach for assigning orthologs between closely related genomes which essentially attempts to transform one genome into another by the smallest number of genome rearrangement events including reversal, translocation, fusion, and fission, as well as gene duplication events. The project addresses three key algorithmic problems including (i) signed reversal distance with duplicates, (ii) signed transposition distance with duplicates, and (iii) minimum common string partition. Efficient solutions to each of these problems are combined and incorporated into a software system for ortholog assignment, called MSOAR . The project encompasses genome-wide analysis of orthologous (and paralogous) relationships on the human and mouse genomes to valdiate the approach, and more importantly, to address several important evolutionary biological questions including the characterization of gains and losses of duplicated genes in the two genomes, the elucidation of gene movements in one genome with respect to the other genome, and the quantification of different mechanisms of gene duplication.

Principal Investigators:

Tao Jiang (PI)
Liqing Zhang (co-PI). (Please see the project site at Virginia Tech.)

Graduate Students and Alumni at UCR:

Guanqun (Wilson) Shi
Meng-Chih (Vincent) Peng
Zheng Fu (alumnus)

Publications:

Z. Fu and T. Jiang. Clustering of main orthologs for multiple genomes. Journal of Bioinformatics and Computational Biology (JBCB), in press; an extended abstract of the same paper has also appeared in Proc. 6th LSS Computational Systems Bioinformatics Conference (CSB), San Diego, 2007, pp. 195-202.

X. Chen, L. Guo, Z. Fan, and T. Jiang. W-AlignACE: An improved Gibbs sampling algorithm based on more accurate position weight matrices. Bioinformatics, in press.

Z. Fu, X. Chen, V. Vacic, P. Nan, Y. Zhong, and T. Jiang. MSOAR: A high-throughput ortholog assignment system based on genome rearrangement. Journal of Computational Biology 14(9), pp. 1160-1175, 2007.

Z. Fu and T. Jiang. Computing the breakpoint distance between partially ordered genomes. Journal of Bioinformatics and Computational Biology (JBCB) 5(5), pp. 1087-1101, 2007.

J. Feng, R. Jiang and T. Jiang. A Max-Flow Based Approach to the Identification of Protein Complexes Using Protein Interaction and Microarray Data (Extended Abstract). Proc. 7th LSS Computational Systems Bioinformatics Conference (CSB), Stanford, August 25-29, 2008.

J. Xiao, L. Wang, X. Liu, and T. Jiang. Finding additive biclusters with random background. Proc. 19th Symposium on Combinatorial Pattern Matching (CPM), Pisa, Italy, June 18-20, 2008.

X. Chen, L. Liu, Z. Liu and T. Jiang. On the minimum common integer partition problem. ACM Transactions on Algorithms (TALG), accepted May 2008.

Funding Sources:

This project is funded by an NSF grant IIS-0711129 for the period of Sept. 15, 2007 - August 31, 2010. A collaborative grant was simultaneously awarded to the co-PI Prof. Liqing Zhang for the same period.

The page was last updated on June 23, 2008.