Department of Genetics Publications for March 21-April 3, 2021
April 5, 2021
Department of Genetics faculty, postdocs, students and collaborators published fifteen papers during March 21-April 3, 2021.
Tag: Jiang
Yuchao Jiang, PhD Awarded R35 Outstanding Investigator Grant from NIGMS
September 3, 2020
Dr. Yuchao Jiang (Assistant Professor of Biostatistics and Genetics) was awarded an R35 grant from the National Institute of General Medical Sciences (NIGMS) for his project titled 鈥淪tatistical Methods for Bulk-Tissue and Single-Cell Multi-Omics Integration鈥�.
Department of Genetics Publications for July 12-25, 2020
July 27, 2020
Department of Genetics faculty, postdocs, students and collaborators published twelve papers during July 12-25, 2020.
Department of Genetics Publications for May 17-30, 2020
June 1, 2020
Department of Genetics faculty, postdocs, students and collaborators published eleven papers during May 17-30, 2020.
Yuchao Jiang, PhD Wins Teaching Excellence and Innovation Award
April 14, 2020
Dr. Yuchao Jiang, Assistant Professor in Biostatistics and Genetics, was recognized for Teaching Excellence and Innovation in Biostatistics by the Gillings School of Public Health (student-nominated).
Department of Genetics Publications for Jan. 12-25, 2020
January 27, 2020
Department of Genetics faculty, postdocs, students and collaborators published seven papers during Jan. 12-25, 2020.
Department of Genetics Publications for Nov. 17-30, 2019
December 4, 2019
Department of Genetics faculty, postdocs, students and collaborators published seventeen papers during Nov. 17-30, 2019.
Yuchao Jiang, PhD Receives 黑料网 Computational Medicine Program Pilot Award
January 11, 2019
Dr. Jiang and co-PI Qing Zhang, PhD (Dept. of Pathology and Laboratory Medicine) received the one-year award to develop single cell -omic analysis tools.
Yuchao Jiang, PhD Receives Junior Faculty Development Award
December 18, 2018
Dr. Jiang's awarded project is titled 鈥淪ingle-Cell Omics for Assessing Genomic, Transcriptomic and Epigenomic Cancer Heterogeneity鈥� and the proposed work aims to develop new statistical methods and computational algorithms for single-cell omic analyses in cancer.