Papers

Google Scholar — Complete publication list

• TargetSage: Identifying Therapeutic Target Genes with Interpretable and Robust LLM Reasoning

  Ziheng Duan, Tong Wu, Xi Li, Simon Dongbo Sun, Chaoyang Wang, Junhao Liu, Martin Renqiang Min, Jing Zhang

  NeurIPS · 2026 · Accepted

  • AI/ML
  • Perturbation / Therapeutic Discovery

• sMMC-22M: A Context-Aware Dataset and Benchmark for Single-Cell Spatial Transcriptomics

  Xi Li, Yaqi Hu, Ziheng Duan, Xinyi Wang, Simon Dongbo Sun, Diptanshu Sikdar, Yang Liu, Jing Zhang

  NeurIPS · 2026 · Accepted

  • AI/ML for Single-Cell & Spatial

• Single-cell transcriptomic and chromatin dynamics of the human brain in PTSD

  Ahyeon Hwang, Mario Skarica, Siwei Xu, et al.

  Nature · 2025

  • Human Disease Genomics
  • Gene Regulation

  • Paper: Single-cell transcriptomic and chromatin dynamics of the human brain in PTSD

• Single-cell genomics and regulatory networks for 388 human brains

  Prashant S. Emani, Jason J. Liu, Declan Clarke, et al.

  Science · 2024

  • Gene Regulation
  • Human Disease Genomics

  • Paper: Single-cell genomics and regulatory networks for 388 human brains

• MUGO: Differentiable Combinatorial Optimization for Causal Variant Discovery in the Non-coding Genome

  Simon Dongbo Sun, Junhao Liu, Pengcheng Xu, Yaqi Hu, Martin Jinye Zhang, Jing Zhang

  KDD · 2026 · Accepted

  • Gene Regulation
  • Perturbation / Therapeutic Discovery

• Identifying Combinatorial Regulatory Genes for Cell Fate Decision via Reparameterizable Subset Explanations

  Junhao Liu, Pengpeng Zhang, Martin Renqiang Min, Jing Zhang

  KDD · 2025

  • AI/ML for Single-Cell & Spatial
  • Perturbation / Therapeutic Discovery

  • Paper: Identifying Combinatorial Regulatory Genes for Cell Fate Decision via Reparameterizable Subset Explanations

• TargetSage: Identifying Therapeutic Target Genes with Interpretable and Robust LLM Reasoning

  Ziheng Duan, Tong Wu, Xi Li, Simon Dongbo Sun, Chaoyang Wang, Junhao Liu, Martin Renqiang Min, Jing Zhang

  NeurIPS · 2026 · Accepted

  • AI/ML
  • Perturbation / Therapeutic Discovery

• sMMC-22M: A Context-Aware Dataset and Benchmark for Single-Cell Spatial Transcriptomics

  Xi Li, Yaqi Hu, Ziheng Duan, Xinyi Wang, Simon Dongbo Sun, Diptanshu Sikdar, Yang Liu, Jing Zhang

  NeurIPS · 2026 · Accepted

  • AI/ML for Single-Cell & Spatial

• Central amygdala single-nucleus atlas reveals chromatin and gene transcription dynamics in human alcohol use disorder

  Che Yu Lee, Ahyeon Hwang, Delaney McRiley, et al.

  Nature Communications · 2026

  • Human Disease Genomics
  • Gene Regulation

  • Paper: Central amygdala single-nucleus atlas reveals chromatin and gene transcription dynamics in human alcohol use disorder

• MUGO: Differentiable Combinatorial Optimization for Causal Variant Discovery in the Non-coding Genome

  Simon Dongbo Sun, Junhao Liu, Pengcheng Xu, Yaqi Hu, Martin Jinye Zhang, Jing Zhang

  KDD · 2026 · Accepted

  • Gene Regulation
  • Perturbation / Therapeutic Discovery

• Single-cell transcriptomic and chromatin dynamics of the human brain in PTSD

  Ahyeon Hwang, Mario Skarica, Siwei Xu, et al.

  Nature · 2025

  • Human Disease Genomics
  • Gene Regulation

  • Paper: Single-cell transcriptomic and chromatin dynamics of the human brain in PTSD

• Single-cell omics arena: evaluation of large language models for automatic cell-type annotations on single-cell omics data via RNA-seq bridging

  Junhao Liu, Siwei Xu, Yongxian Wu, Jing Zhang

  Briefings in Bioinformatics · 2025

  • AI/ML for Single-Cell & Spatial

  • Paper: Single-cell omics arena: evaluation of large language models for automatic cell-type annotations on single-cell omics data via RNA-seq bridging

• MUSE: A Multi-slice Joint Analysis Method for Spatial Transcriptomics Experiments

  Ziheng Duan, Xi Li, Zhiqing Xiao, Rex Ying, Jing Zhang

  CIKM · 2025

  • AI/ML for Single-Cell & Spatial

  • Paper: MUSE: A Multi-slice Joint Analysis Method for Spatial Transcriptomics Experiments

• Identifying Combinatorial Regulatory Genes for Cell Fate Decision via Reparameterizable Subset Explanations

  Junhao Liu, Pengpeng Zhang, Martin Renqiang Min, Jing Zhang

  KDD · 2025

  • AI/ML for Single-Cell & Spatial
  • Perturbation / Therapeutic Discovery

  • Paper: Identifying Combinatorial Regulatory Genes for Cell Fate Decision via Reparameterizable Subset Explanations

• scACT: Accurate Cross-modality Translation via Cycle-consistent Training from Unpaired Single-cell Data

  Siwei Xu, Junhao Liu, Jing Zhang

  CIKM · 2024

  • AI/ML for Single-Cell & Spatial
  • Gene Regulation

  • Paper: scACT: Accurate Cross-modality Translation via Cycle-consistent Training from Unpaired Single-cell Data

• scENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding

  Ziheng Duan, Siwei Xu, Shushrruth Sai Srinivasan, et al.

  Briefings in Bioinformatics · 2024

  • AI/ML for Single-Cell & Spatial
  • Gene Regulation

  • Paper: scENCORE: leveraging single-cell epigenetic data to predict chromatin conformation using graph embedding

• iMIRACLE: An Iterative Multi-View Graph Neural Network to Model Intercellular Gene Regulation from Spatial Transcriptomic Data

  Ziheng Duan, Siwei Xu, Cheyu Lee, Dylan Riffle, Jing Zhang

  CIKM · 2024

  • AI/ML for Single-Cell & Spatial
  • Gene Regulation

  • Paper: iMIRACLE: An Iterative Multi-View Graph Neural Network to Model Intercellular Gene Regulation from Spatial Transcriptomic Data

• Impeller: a path-based heterogeneous graph learning method for spatial transcriptomic data imputation

  Ziheng Duan, Dylan Riffle, Ren Li, Junhao Liu, Martin Renqiang Min, Jing Zhang

  Bioinformatics · 2024

  • AI/ML for Single-Cell & Spatial

  • Paper: Impeller: a path-based heterogeneous graph learning method for spatial transcriptomic data imputation

• Single-cell genomics and regulatory networks for 388 human brains

  Prashant S. Emani, Jason J. Liu, Declan Clarke, et al.

  Science · 2024

  • Gene Regulation
  • Human Disease Genomics

  • Paper: Single-cell genomics and regulatory networks for 388 human brains

• iHerd: an integrative hierarchical graph representation learning framework to quantify network changes and prioritize risk genes in disease

  Ziheng Duan, Yi Dai, Ahyeon Hwang, Cheyu Lee, Kaichi Xie, Chutong Xiao, Min Xu, Matthew J. Girgenti, Jing Zhang

  PLOS Computational Biology · 2023

  • Gene Regulation
  • Human Disease Genomics

  • Paper: iHerd: an integrative hierarchical graph representation learning framework to quantify network changes and prioritize risk genes in disease

• DeepVelo: Single-cell transcriptomic deep velocity field learning with neural ordinary differential equations

  Zhanlin Chen, William C. King, Aheyon Hwang, Mark Gerstein, Jing Zhang

  Science Advances · 2022

  • AI/ML for Single-Cell & Spatial
  • Perturbation / Therapeutic Discovery

  • Paper: DeepVelo: Single-cell transcriptomic deep velocity field learning with neural ordinary differential equations

• DIRECT-NET: An efficient method to discover cis-regulatory elements and construct regulatory networks from single-cell multiomics data

  Lihua Zhang, Jing Zhang, Qing Nie

  Science Advances · 2022

  • AI/ML for Single-Cell & Spatial
  • Gene Regulation

  • Paper: DIRECT-NET: An efficient method to discover cis-regulatory elements and construct regulatory networks from single-cell multiomics data