Decoding the human genome and others closely related to it is our primary research interest, and comparative genomics and integrated analysis of functional genomics data are our major research approaches. In general, we are interested in developing and applying computational methods for exploiting patterns in high-throughput genomic data and for integrating information from experimental and computational biology. We are highly interested in studying the expression, regulation, and evolution of human nervous systems genes (coding or noncoding), especially those implicated in neurodegenerative diseases, using experimental data from next-generation sequencing (e.g., ChIP-Seq and RNA-Seq). Specifically, our research group will be focused on these areas:
+ Gene duplication, to investigate how gene duplication has shaped the human genome and how novel genes or regulatory elements emerge in humans and other primates.
Gene expansion (through either duplication or retrotransposition) is a major driving force for the emergence of novel functions during evolution. Inter- and intra-genome sequence comparison can reveal DNA elements that are either uniquely present or specifically selected in certain species. Tracking the evolutionary history of such sequences can lead to the discovery of genes or regulatory elements (including non-coding RNAs) that function specifically in humans. Thus, the long-term goal is to search for functional genomic components that set us apart from other animals. To this end, our research will compare the human genome with other mammalian (e.g., chimp, macaque, dog, and mouse) genomes to exploit the role of gene duplication in generating novel protein-protein interactions and novel biochemical pathways. We are interested in both the birth and the death (pseudogenization or loss) of such lineage-specific functional DNA sequences, especially for those involved in the development of nervous system and brains.
+ Integrated analysis of functional genomics data, to explore computational techniques for combining experimental and computational genomics data in order to achieve a global understanding of the function of the human genome.
We are interested in developing bioinformatics algorithms to conduct cross-genome sequence comparisons (e.g., ortholog assignment) with a focus on aims of our specific research. As large amount of functional genomic data from diverse sources (microarray, high-throughput sequencing, protein-protein interaction, etc.) will be used in our studies, our group plan to develop effective computational methods for data integration and at the same time for addressing common concerns of data quality in genome-scale experiments. A rigorous statistical framework needs to be built in order to extract biologically meaningful signals from noises or stochastic background.
+ Functional implication of alternative splicing, to investigate how higher eukaryotes (e.g., humans) achieve functional diversity through producing multiple RNA transcripts from one gene locus.
We are particularly interested in the generation of isoforms in different tissues / cells and how these special isoforms carry out their tissue-specific functions.
Education
- YALE UNIVERSITY, New Haven, CT. 2003-2007, Postdoctoral Fellow, Department of Molecular Biophysics and Biochemistry. Research Area: Bioinformatics & Human Genomics.
- RUTGERS UNIVERSITY, Piscataway, NJ. Ph.D. in Biochemistry, 2003. Rsearch Area: Structural Genomics & Bioinformatics.
- AUBURN UNIVERSITY, Auburn, AL. M.S. in Pathobiology, 1998. Research Area: Molecular Biology.
- BEIJING AGRICULTURAL UNIVERSITY, Beijing, China. B.S. in Microbiology, 1992
Resume
+ Xingyi Guo, Postdoctoral Associate.
We are looking for enthusiastic undergraduate students, graduate students, and postdoctoral associates to join our group. Reasonable computer programming skills is a plus. Candidates are expected to work in a wide range of bioinformatics projects. Please contact the PI, Deyou Zheng, for details.
(*corresponding author)