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<\/p>\nDr. Jiang joined UNC in July 2017 as an Assistant Professor in the Departments of Biostatistics and Genetics.\u00a0 His primary research interests are focused on statistical modeling, method development and data analysis in genetics and genomics.<\/p>\n
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His awarded project is titled \u201cSingle-Cell Omics for Assessing Genomic, Transcriptomic and Epigenomic Cancer Heterogeneity\u201d and the proposed work aims to develop new statistical methods and computational algorithms for single-cell omic analyses in cancer.\u00a0 Cancer is a disease driven by rounds of genetic and epigenetic mutations that follow Darwinian evolution. The tumor for a given patient is often a mixture of genotypically and phenotypically distinct cell populations. This contributes to failures of targeted therapies and to drug resistance, rendering the importance of studying intra-tumor heterogeneity.\u00a0Single-cell sequencing circumvents the averaging artifacts associated with traditional bulk population data and has seen rapid technological developments over the past few years.\u00a0 His lab plans to develop methods to profile copy number aberrations and assess intratumor heterogeneity by single-cell DNA sequencing, to deconvolute bulk gene expression profiles by existing single-cell RNA sequencing datasets, and to profile epigenetic heterogeneity by single-cell chromatin accessibility analysis. They will apply methods to both bulk-tissue and single-cell cancer sequencing datasets that are either publicly available or generated through collaborations. Through this framework, the lab will be able to extract genomic, transcriptomic, and epigenomic signatures, which will greatly facilitate understanding of tumor progression and metastasis, aid biomarker discovery for diagnosis, and tailor personalized treatment.<\/p>\n","protected":false},"excerpt":{"rendered":"
Dr. Jiang’s awarded project is titled \u201cSingle-Cell Omics for Assessing Genomic, Transcriptomic and Epigenomic Cancer Heterogeneity\u201d and the proposed work aims to develop new statistical methods and computational algorithms for single-cell omic analyses in cancer.<\/p>\n","protected":false},"author":28418,"featured_media":6608,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[2],"tags":[29,31,28],"class_list":["post-6607","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-bcb","tag-jiang","tag-unc-genetics","odd"],"acf":[],"yoast_head":"\n