Yawen Zhang: lecturer
　　Email: yawen@ujs.edu.cn

　　Educational background
　　2015.09 ~ 2021.06: Hua Zhong Agricultural University, Crop genetics and breeding, Ph.D
　　2011.09 ~ 2015.06: Fujian Agriculture and Forestry University, bachelor

　　Academic background
　　2023.06 ~ Now, Jiangsu University, International Genome Center.
　　2023.07 ~ Now, Hua Zhong Agricultural University, Postdoctoral Researcher of Plant Protection

　　Research fields
　　Mixed liner model of Genome Wide Association Study.

　　Key scientific research projects
　　1.New methodologies and software for detecting QTLs and QTL-by-environment interactions of resistance traits in bi-parental segregation populations. (supported by National Natural Science Foundation of China youth science fund projects)
　　2.New methodologies and software for compressed variance component mixed model of Genome Wide Association Study in Colorectal cancer. (supported by Chinese Postdoctoral Science Foundation)

　　Publications
　　1.Zhang Ya-Wen#, Tamba Cox Lwaka#, Wen Yang-Jun, Li Pei, Ren Wen-Long, Ni Yuan-Li, Gao Jun, Zhang Yuan-Ming*. mrMLM v4.0.2: An R platform for multi-locus genome-wide association studies. Genomics Proteomics Bioinformatics, 2020, 18:481-487
　　2.Zhang Ya-Wen, Wen Yang-Jun, Dunwell J M, Zhang Yuan-Ming*. QTL.gCIMapping.GUI v2.0: An R software for detecting small-effect and linked QTLs for quantitative traits in bi-parental segregation populations. Comput Struct Biotechnol J, 2020, 18:59-65.
　　3.Zhao Qiong, Shi Xiao-Shi, Wang Tian, Chen Ying, Yang Rui, Mi Jiaming*, Zhang Ya-Wen*, Zhang Yuan-Ming. Identification of QTNs, QTN-by-environment interactions, and their candidate genes for grain size traits in main crop and ratoon rice. Front Plant Sci, 2023, 14: 1119218.
　　4.Li Mei#, Zhang Ya-Wen#, Zhang Ze-Chang, Xiang Yu, Liu Ming-Hui, Zhou Ya-Hui, Zuo Jian-Fang, Zhang Han-Qing, Chen-Ying, Zhang Yuan-Ming*. A compressed variance component mixed model for detecting QTNs, and QTN-by-environment and QTN-by-QTN interactions in genome-wide association studies. Molecular Plant, 2022,15:630-650.
　　5.Liu Jin-Yang#, Zhang Ya-Wen#, Han Xu, Zuo Jian-Fang, Zhang Zhi-Bin, Shang Hai-Hong, Song Qi-Jian, Zhang Yuan-Ming*. An evolutionary population structure model reveals pleiotropic effects of GmPDAT for traits related to seed size and oil content in soybean. J Exp Bot, 2020, 71:6988-7002.
　　6.Li Jie-Qin#, Tang Wei-Jie#, Zhang Ya-Wen#, Chen Kai-Ning, Wang Chen-Chen, Liu Yan-Long, Zhan Qiu-Wen, Wang Chun-Ming, Wang Shi-Bo, Xie Shang-Qian*, Wang Li-Hua*. Genome-wide association studies for five forage quality-related traits in sorghum (Sorghum bicolor L.). Front Plant Sci, 2018, 9:1146.
　　7.Li Mei, Zhang Ya-Wen, Xiang Yu, Liu Ming-Hui, Zhang Yuan-Ming. IIIVmrMLM: the R and C++ tools associated with 3VmrMLM, a comprehensive GWAS method for dissecting quantitative traits. Mol Plant, 2022, 15: 1251–1253.
　　8.Wen Yang-Jun, Zhang Ya-Wen, Zhang Jin, Feng Jian-Ying, Dunwell Jim M, Zhang Yuan-Ming*. An efficient multi-locus mixed model framework for the detection of small and linked QTLs in F2. Brief Bioinform, 2019, 20:1913-1924.
　　9.Han Xu, Zhang Ya-Wen, Liu Jin-Yang, Zuo Jian-Fang, Zhang Ze-Chang, Guo Liang*, Zhang Yuan-Ming*. 4D genetic networks reveal the genetic basis of metabolites and seed oil-related traits in 398 soybean RILs. Biotechnol Biofuels Bioprod, 2022, 15:92.
　　10.Wen Yang-Jun, Zhang Ya-Wen, Zhang Jin, Feng Jian-ying, Zhang Yuan-Ming*. The improved FASTmrEMMA and GCIM algorithms for genome-wide association and linkage studies in large mapping populations. The Crop Journal, 2020, 8:723-732.