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Research Interest (Keyword Cloud )
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We are interested in the
broad area of bioinformatics, systems medicine, personalized medicine, and translational science. We develop
independent research projects to study important biological
problems. We also actively collaborate with
investigators university-wide, nationally and
internationally. Our current research topics are:
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Next generation sequencing (NGS) data analysis
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Since 2009, our lab quickly moved to develop pipelines for NGS data analysis. We are the first one being able to analyze the whole genome sequencing data in Vanderbilt. We currently analyzed data generated by Illumina (RNA-Seq, WGS, Exomes), SOLiD, and 454 platforms and for diseases such as melanoma, sever types of lung cancer including drug resistance, schizophrenia, bipolar disorder, Pulmonary Arterial Hypertension (PAH), Idiopathic Pulmonary Fibrosis (IPF), breast cancer, and colorectal cancer, among many others. Current projects also include analysis of the RNA-Seq data in yeast and ChIP-Seq. Our collaborators are both within the Vanderbilt University Medical Center, Vanderbilt-Ingram Cancer Center, and outside (Yale University, MGH, Harvard, Georgetown University, University of Southern California, Virginia Commonwealth University, Chinese Academy of Sciences, etc.). We are also actively developing our NGS analysis pipelines, The NGS Catalog database , and other computational tools. A list of recent NGS publications or manuscripts can be accessed here.
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Disease gene network/pathway analysis
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Molecular mechanisms of complex diseases are much more
complicated than previous thought. Rather than the traditional
approaches to studying single genes or locus, we investigate
gene networks/pathways in complex diseases especially in
psychiatric disorders and cancer. This includes protein-protein
interaction (PPI) networks, biological pathways, pathway
crosstalk, molecular network analysis by combing PPIs and
pathways, and regulatory networks (e.g. microRNA and
transcription factor mediated networks).
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Translational Bioinformatics
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Integrative analyses of pharmacogenomics datasets and electronic medical records (EMRs), network pharmacology, application of systems biology approaches to identify biomarkers for drug response and side effects.
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Cancer bioinformatics
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Noncoding RNA genes in cancer; gene fusion using Next-Gen sequencing technology; microarray gene expression profiling (GEP) in differnet cancer/tumors; GWAS analysis in cancer studies; methylation pattern in cancer cell lines or tumor tissues; and investigation of methylation
status in tissue-specific genes.
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Data integration and mining
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This involves data collection and curation, data management,
integration, gene ranking, and gene feature analysis. We are
specifically interested in integration of multi-dimensional
data for specific disease. This includes (1) various types of
genetic data such as linkage scan, gene expression, association
studies, and genome-wide association studies (GWAS), (2)
biological data such as Gene Ontology annotations,
protein-protein interactions, and pathways, and (3)
phenotypes/traits. We also develop computational tools and
databases.
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Bioinformatics in psychiatric genetics
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Study of gene structures of schizophrenia susceptibility genes
(e.g. DTNBP1); design and establishment of a comprehensive
bioinformatics system to efficiently manage various types of
data; and development of computational tools for lab
experimental support (e.g. selection of candidate genes or
genetic markers).
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Comparative and evolutionary genomics
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Investigation and comparison of patterns of single nucleotide
polymorphisms (SNPs) among mammalian genomes and in their
specific genomic regions; comparative genomic analysis of
sequences especially CpG island sequences.
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Human population genetics
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Patterns of genetic variation, genotype, and haplotype within
and between subpopulations; and evolutionary history of human
population.
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Students and post-doctoral fellows
are always encouraged to develop their own projects in the
broad area of bioinformatics.
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