I am currently a fourth-year PhD candidate in Dr. James Schnable's lab from University of Nebraska-Lincoln. Before that, I worked in rice molecular biology in Mississippi State University and I got my Bachelor degree from Nanjing Agricultural University in China. My current research interests focus on plant high-throughput phenotyping, comparative grass genomics, as well as integrating omics data to reveal genetic questions in crop species, like maize, sorghum and setaria.
Research Areas: Computational Biology, Phenomics, Genetics
1. Liang Z, Qiu Y, Schnable JC (2019) Distinct Characteristics of Genes Associated with Phenome-Wide Variation in Maize (Zea mays). bioRxiv. doi: 10.1101/534503
2. Liang Z, Gupta SK, Yeh CT,...,Yang J,Varshney RK, Schnable PS, Schnable JC (2018) Impact of combining phenotypic data from hybrid and inbred pearl millet lines to genomic selection guided evaluation of potential crosses. G3: Genes|Genomes|Genetics doi:10.1534/g3.118.200242
3. Liang Z, Schnable JC (2018) Functional Divergence Between Subgenomes and Gene Pairs After Whole Genome Duplications. Molecular Plant doi:10.1016/j.molp.2017.12.010
4. Liang Z, Pandey P, Stoerger V, Xu Y, Qiu Y, Ge Y, Schnable JC (2017) Conventional and hyperspectral time-series imaging of maize lines widely used in field trials. GigaScience doi:10.1093/gigascience/gix117
5. Zhang Y, Ngu DW, Carvalho D, Liang Z, Qiu Y, Roston RL, Schnable JC (2017) Differentially Regulated Orthologs in Sorghum and the Subgenomes of Maize. The Plant Cell doi: 10.1105/tpc.17.00354
6. Lai X*, Behera B*, Liang Z, Lu Y, Deogun JS, Schnable JC (2017) STAG-CNS: An Order-Aware Conserved Non-coding Sequences Discovery Tool For Arbitrary Numbers of Species. Molecular Plant doi: 10.1016/j.molp.2017.05.010.
7. Choudhury SD, Samal A, Stoerger V, Schnable JC, Liang Z, Yu J (2016) Automated Vegetative Stage Phenotyping Analysis of Maize Plants using Visible Light Images. 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining. San Francisco, California, USA
8. Liang Z, Schnable JC (2016) RNA-seq based analysis of population structure within the maize inbred B73. PloS ONE doi:10.1371/journal.pone.0157942
9. Lv Y, Liang Z, Ge M, Qi W, Zhang T, Lin F, Peng Z, Zhao H (2016) Genome-wide identification and functional prediction of nitrogen-responsive intergenic and intronic long non-coding RNAs in maize (Zea mays L.). BMC Genomics doi:10.1186/s12864-016-2650-1
10. Zhang Y, Zheng J, Liang Z, Liang Y, Peng Z, Wang C. (2015) Verification and evaluation of grain QTLs using RILs from TD70 x Kasalath in rice. Genet Mol Res doi:10.4238/2015.November.18.53
1. Fascination of Plants Day 2017. Demonstrated the CoGe Comparative Genomic Tool to High School Student.
2. "Sunday with a scientist" Educated children on measuring plant phenotypes from computer vision.