Jian Zhou, Ph.D.

Since November 2019, Jian Zhou has been appointed as Assistant Professor in the Lyda Hill Department of Bioinformatics. He is a Lupe Murchison Foundation Scholar in Medical Research and is a Scholar of the Cancer Prevention and Research Institute of Texas (CPRIT). Prior to joining UTSW, he was a Flatiron Research Fellow at the Center of Computational Biology at Flatiron Institute, New York. He received his B.S. in Biological Sciences from Peking University and Ph.D. in Quantitative and Computational Biology from Princeton University.

The Zhou lab works at the intersection of machine learning and genomics. The lab develops computational methods to improve our understanding of genome-based regulation and the genetic basis of human health and diseases.  Advancing machine learning and AI methods for science, especially genomics is a long-term goal of the lab. Visit the lab website for more details https://zhoulab.io.

• Decipher gene regulatory program from genomic sequence
• Developing computational methods for advancing single-cell data analysis
• Improving machine learning & AI methods for science
• Sequence-based modeling of 3D genome organization
• Understand evolution of the regulatory genome

Featured Publications

Sequence-based modeling of three-dimensional genome architecture from kilobase to chromosome scale.

Zhou J, Nat Genet 2022 May 54 5 725-734

An analytical framework for interpretable and generalizable single-cell data analysis.

Zhou J, Troyanskaya OG, Nat Methods 2021 Nov 18 11 1317-1321

Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk.

Zhou J, Park CY, Theesfeld CL, Wong AK, Yuan Y, Scheckel C, Fak JJ, Funk J, Yao K, Tajima Y, Packer A, Darnell RB, Troyanskaya OG, Nat. Genet. 2019 06 51 6 973-980

Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk.

Zhou J, Theesfeld CL, Yao K, Chen KM, Wong AK, Troyanskaya OG, Nat. Genet. 2018 08 50 8 1171-1179

Predicting effects of noncoding variants with deep learning-based sequence model.

Zhou J, Troyanskaya OG, Nat. Methods 2015 Oct 12 10 931-4

Genome-wide landscape of RNA-binding protein target site dysregulation reveals a major impact on psychiatric disorder risk.

Park CY, Zhou J, Wong AK, Chen KM, Theesfeld CL, Darnell RB, Troyanskaya OG, Nat Genet 2021 02 53 2 166-173

Genomic analyses implicate noncoding de novo variants in congenital heart disease.

Richter F, Morton SU, Kim SW, Kitaygorodsky A, Wasson LK, Chen KM, Zhou J, Qi H, Patel N, DePalma SR, Parfenov M, Homsy J, Gorham JM, Manheimer KB, Velinder M, Farrell A, Marth G, Schadt EE, Kaltman JR, Newburger JW, Giardini A, Goldmuntz E, Brueckner M, Kim R, Porter GA, Bernstein D, Chung WK, Srivastava D, Tristani-Firouzi M, Troyanskaya OG, Dickel DE, Shen Y, Seidman JG, Seidman CE, Gelb BD, Nat Genet 2020 08 52 8 769-777

Accurate genome-wide predictions of spatio-temporal gene expression during embryonic development.

Zhou J, Schor IE, Yao V, Theesfeld CL, Marco-Ferreres R, Tadych A, Furlong EEM, Troyanskaya OG, PLoS Genet. 2019 Sep 15 9 e1008382

Selene: a PyTorch-based deep learning library for sequence data.

Chen KM, Cofer EM, Zhou J, Troyanskaya OG, Nat. Methods 2019 04 16 4 315-318

New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries.

Shrine N, Guyatt AL, Erzurumluoglu AM, Jackson VE, Hobbs BD, Melbourne CA, Batini C, Fawcett KA, Song K, Sakornsakolpat P, Li X, Boxall R, Reeve NF, Obeidat M, Zhao JH, Wielscher M, Weiss S, Kentistou KA, Cook JP, Sun BB, Zhou J, Hui J, Karrasch S, Imboden M, Harris SE, Marten J, Enroth S, Kerr SM, Surakka I, Vitart V, Lehtimäki T, Allen RJ, Bakke PS, Beaty TH, Bleecker ER, Bossé Y, Brandsma CA, Chen Z, Crapo JD, Danesh J, DeMeo DL, Dudbridge F, Ewert R, Gieger C, Gulsvik A, Hansell AL, Hao K, Hoffman JD, Hokanson JE, Homuth G, Joshi PK, Joubert P, Langenberg C, Li X, Li L, Lin K, Lind L, Locantore N, Luan J, Mahajan A, Maranville JC, Murray A, Nickle DC, Packer R, Parker MM, Paynton ML, Porteous DJ, Prokopenko D, Qiao D, Rawal R, Runz H, Sayers I, Sin DD, Smith BH, Soler Artigas M, Sparrow D, Tal-Singer R, Timmers PRHJ, Van den Berge M, Whittaker JC, Woodruff PG, Yerges-Armstrong LM, Troyanskaya OG, Raitakari OT, Kähönen M, Pola?ek O, Gyllensten U, Rudan I, Deary IJ, Probst-Hensch NM, Schulz H, James AL, Wilson JF, Stubbe B, Zeggini E, Jarvelin MR, Wareham N, Silverman EK, Hayward C, Morris AP, Butterworth AS, Scott RA, Walters RG, Meyers DA, Cho MH, Strachan DP, Hall IP, Tobin MD, Wain LV, Nat. Genet. 2019 03 51 3 481-493

• NIH Director's New Innovator Award
  (2021)