My research has focused on pathway analysis and relevant software development, including enrichment analysis, construction and modeling. I integrated appropriate pathway databases and effective gene mapping methods to improve the identification of relevant pathways in high-throughput data. I also constructed some interested biological pathways using orthologous gene mapping and functional relation information. Currently, I am interested in predictive pathway modeling to guide experimental design and hypothesis generation, especially in biofuel study.

Pathway Reconstruction

There have been a number of public high-quality pathway database, but they are not yet complete. I have developed a new method to include more relevant genes as possibly by integrating well-known pathway databases and functional relation prediction, such co-operon, co-PPI, co-expression and co-evolution. I have also developed an intuitive web server for automating the process of such pathway construction.

References:

  • Xizeng Mao, Victor Olman, Rhona Stuart, Ian Paulsen, Brian Palenik, and Ying Xu. 2010. Computational prediction of the osmoregulation network in Synechococcus sp. WH8102. BMC Genomics 11, no. 1: 291.
  • Xizeng Mao, Xin Chen, Yu Zhang and Ying Xu. CINPER: an interactive knowledge-based web platform for automated construction of biological pathways for prokaryotes. In preparation, 2011. Web server

Pathway enrichment analysis

Pathway enrichment analysis is an important approach to characterize important pathways in high-throughput data such as microarray, proteiomics and next generation sequencing. The effectiveness of this method is highly affected by the coverage (generally, 1/3 of gene set are only annotated by KEGG pathway) and accuracy of pathway annotation. Compared to other methods using individual pathway databases and gene ID mapping method, I integrated multiple high-quality pathways databases and ortholog / homolog search methods to improve both annotation coverage and accuracy. I have developed the intuitive and effective command line and web tools to help users to use these methods quickly.

References:

  • Xizeng Mao*, Yu Zhang*, and Ying Xu. 2011. SEAS: SEED-based Enrichment Analysis System for Prokaryotes. PLoS ONE 6(7): e22556. doi:10.1371/journal.pone.0022556. Download.
  • Chen Xie, Xizeng Mao, Jiaju Huang, Yang Ding, Jianmin Wu, Shan Dong, Lei Kong, Ge Gao, Chuan-Yun Li, Liping Wei. KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucl. Acids Res. (2011) 39(suppl 2): W316-W322 doi:10.1093/nar/gkr483. Web server
  • Wu, J.*, Mao, Xizeng.*, Cai, T., Luo, J., Wei, L. (2006) KOBAS server: a web-based platform for automated annotation and pathway identification. Nucleic Acids Res. 2006; 34:W720-W724. Web Server URL: http://kobas.cbi.pku.edu.cn. (Cited by 58 Google Scholar, Jul. 30, 2011)
  • Mao Xizeng.*, Cai T.*, Olyarchuk J.G. and Wei L. (2005) Automated Genome Annotation and Pathway Identification Using the KEGG Orthology (KO) As a Controlled Vocabulary, Bioinformatics, 21:3787-3793.

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