Carnegie Mellon University

jianma_082017.jpeg Jian Ma

Ray and Stephanie Lane Professor of Computational Biology,  Ray and Stephanie Lane Computational Biology Department

Address: 

Ray and Stephanie Lane Computational Biology Department, SCS
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA 15213
Gates Hillman Center Room 7705

Work Phone: 412-268-2776
Administrative Assistant: Ally Ricarte

Email

 

The research in the lab primarily focuses on developing AI/ML methods to study the structure and function of the human genome and cellular organization, with significant implications for health and disease. Recent interests include nuclear organization, single-cell epigenomics, spatial omics, and complex molecular interactions. These goals are often pursued through the development of probabilistic models and advanced deep learning techniques, particularly graph-based representation learning. The group is also actively exploring large language models to uncover gene regulatory mechanisms and the intricate connections among cellular components at various scales in complex tissues. The lab leads an NIH Center in the 4D Nucleome (4DN) Program and is involved in the NIH SenNet Consortium and the IGVF Consortium.

Lab Members

 
Shahul Alam
Ph.D Student
Wenduo Cheng
Ph.D. Student (co-advised by Ameet Talwalkar)
 
Xue Er Ding
Ph.D. Student
 
Nicholas Ho
Ph.D. Student (co-advised by Eric Xing)
 
Ellie Huber
Ph.D. Student (Machine Learning Department)
Spencer Krieger
Lane Fellow
 
Shaoheng Liang
Lane Fellow
 
Reming Liu
Postdoctoral Fellow
 
Xinyue Lu
Ph.D. Student
 
Junjie Tang
Postdoctoral Fellow
 
Shike Wang
Ph.D. Student
 
Muyu Yang
Ph.D. Student
 
Yang Zhang
Project Scientist/Engineer

Highlighted Publications

Chen V#, Yang M#, Cui W, Kim JS, Talwalkar A*, and Ma J*. Applying interpretable machine learning in computational biology - pitfalls, recommendations and opportunities for new developments. Nature Methods, 21(8):1454-1461, 2024.

Xiong K#, Zhang R#, and Ma J. scGHOST: Identifying single-cell 3D genome subcompartments. Nature Methods, 21(5):814-822, 2024.

Zhou T, Zhang R, Jia D, Doty RT, Munday AD, Gao D, Xin L, Abkowitz JL, Duan Z*, and Ma J*. GAGE-seq concurrently profiles multiscale 3D genome organization and gene expression in single cells. Nature Genetics, 56(8):1701-1711, 2024.

Zhang Y, Boninsegna L, Yang M, Misteli T, Alber F, and Ma J. Computational methods for analysing multiscale 3D genome organization. Nature Reviews Genetics, 5(2):123-141, 2024.

Chidester B#, Zhou T#, Alam S, and Ma J. SPICEMIX enables integrative single-cell spatial modeling of cell identity. Nature Genetics, 55(1):78-88, 2023. [Cover Article]

Zhu X#, Zhang Y#, Wang Y, Tian D, Belmont AS, Swedlow JR, and Ma J. Nucleome Browser: An integrative and multimodal data navigation platform for 4D Nucleome. Nature Methods, 19(8):911-913, 2022.


Zhang R, Zhou T, and Ma J. Multiscale and integrative single-cell Hi-C analysis with Higashi. Nature Biotechnology, 40:254–261, 2022.

 

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