Author

Mingqian Ma

Carnegie Mellon University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genomics· 2

Signature Assays, Organisms & Methods

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Assay:DNA methylation· 2 Research Focus:gene regulatory network inference· 2 Organism:human· 2 Organism:bacteria (other)· 1 Approach:contrastive learning· 1 Assay:CRISPR screen· 1 Research Focus:database / resource· 1 Approach:deep learning· 1

Frequent Co-Authors

Bowen ZhouiD· 1 shared Chuan CaoiD· 1 shared Cuiting Zhong· 1 shared Dongxin YeiD· 1 shared Feifei Jiang· 1 shared Guoqing LiuiD· 1 shared Haiguang LiuiD· 1 shared Haitao HuangiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperGenomics

Bowen ZhouORCID

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2 papers

Recent·Most cited

CENO: A Genome-Scale World Model for Evolutionary Sequence Interpretation and Programmable Regulatory Design

Mingqian Ma, Yucheng Wu, Xin Chen, Feifei Jiang, Peijun Lin, Dongxin Ye, Yidi Sun, Yijing Zhang, Tianqiong Shi, Yu Zhao, Wanli Ouyang, Bowen Zhou, Lei Bai, Yuchen Ren

CENO is a long-context generative model for genomic sequence understanding and design, showing improved variant prediction and regulatory sequence generation across species.

bioRxiv · Jul 30, 2026 · PreprintGenomics

Reconstructing sequence-grammar trajectories enables interpretable and tunable cis-regulatory element design

Mingqian Ma, Wanjuan Bu, Guoqing Liu, Yuxuan Liu, Liu S, Zhen Zhao, Shijie Yao, Qingru Hua, Yu Zhang, Cuiting Zhong, Haitao Huang, Pan Deng, Peiran Jin, Qijin Yin, Chuan Cao, , Zeyu Chen

This paper introduces GO-CRE, a method for designing cell-type-specific cis-regulatory elements by reconstructing sequence-grammar trajectories and using reinforcement learning with predictor guidance.

bioRxiv · Jul 17, 2026 · PreprintGenomics