工作经历

范德堡大学医学中心
博士后研究员, 2024/2 - 至今
导师：Dr. Marcela Brissova

研究兴趣
  • 利用统计学和机器学习模型来理解胰岛生物学和糖尿病机制
  • 探索视觉-语言模型在生物医学数据中的应用，特别是在胰岛生物学和糖尿病研究中的潜力
  • 基于知识图谱开发数据整合工具，以联合分析人类的基因组、表观基因组、转录组和四维基因组数据
  • 染色质三维结构模式分析

教育经历

密歇根大学安娜堡分校, 计算药物学与生物信息学系
生物信息学 博士, 2018/9 - 2023/12
导师: Dr. Jie Liu

北京大学, 化学与分子工程学院
化学生物学 学士, 2014/9 - 2018/7
北京大学优秀毕业生/化学与分子工程学院优秀毕业生

北京大学, 国家发展研究院
经济学 双学位学士, 2015/9 - 2018/7

论文发表

已发表: (*表示共同第一作者)
  • Tao., Y., Feng, F., Luo, X., & Liu., J. (2024). CNTools: A computational toolbox for cellular neighborhood analysis from cell images. PLos Computational Biology, 20.8 (2024): e1012344.
  • Zhang, Z., Feng, F., Qiu, Y., & Liu, J. (2023). A generalizable framework to comprehensively predict epigenome, chromatin organization, and transcriptome. Nucleic Acids Research, 51(12), 5931-5947.
  • IGVF Consortium (2024). Deciphering the impact of genomic variation on function. Nature, 633(8028), 47-57.
  • Feng, F., Tang, F., Gao, Y., Zhu, D., ... & Liu, J. (2023). GenomicKB: a knowledge graph for human genomics. Nucleic Acids Research, 51.D1, D950-D956.
  • Zhang, Z., Feng, F., & Liu, J. (2022). Characterizing collaborative transcription regulation with a graph-based deep learning approach. PLoS Computational Biology, 18(6), e1010162.
  • Feng, F., Yao, Y., Wang, X. Q. D., Zhang, X., & Liu, J. (2022). Connecting high-resolution 3D chromatin organization with epigenomics. Nature Communications, 13(1), 1-10.
  • Li, X., Feng, F., Pu, H., Leung, W. Y., & Liu, J. (2021). scHiCTools: A computational toolbox for analyzing single-cell Hi-C data. PLoS Computational Biology, 17(5), e1008978.
  • Himadewi, P.*, Wang, X. Q. D.*, Feng, F.*, Gore, H., Liu, Y., Yu, L., ... & Zhang, X. (2021). 3'HS1 CTCF binding site in human β-globin locus regulates fetal hemoglobin expression. Elife, 10, e70557.
  • Zhang, X., Wang, X. Q. D., Gore, H., Himadewi, P., Feng, F., & Liu, J. (2020). 3D Genomics of Acute Meyloid Leukemia Reveals the Imbalance between DNA Methylation Canyon Interactions and Leukemic Specific Enhancer Network Interactions. Blood, 136, 45.
  • Feng, F., Lai, L., & Pei, J. (2018). Computational chemical synthesis analysis and pathway design. Frontiers in Chemistry, 6, 199.
已提交/审稿中/预印本:
  • Huang, Y., Han, Z., Luo, X., ..., Feng, F., ... & Liu, J. (2024). Building a literature knowledge base towards transparent biomedical AI. (under review by Nature Machine Intelligence)
  • Hong, C. K., Feng, F.*, Ramanathan, V., Liu, J., & Hansen, A. S. (2025). Genome structure mapping with high-resolution 3D genomics and deep learning. (under review by Science)
  • Luo, X., Huang, Y., Tao, Y., Feng, F., Hopkirk, A., Bate, T. S., ... & Liu, J. (2024). CelLink: integrating single-cell multi-omics data with weak feature linkage and imbalanced cell populations. (under review by Nucleic Acids Research)
  • Saunders, D. C., Hart, N., Pan, F. C., ..., Feng, F., ... & Brissova, M. (2024). Mapping histological and functional maturation of human endocrine pancreas across early postnatal periods. (under review by Nature Communications)
  • Evans-Molina, C., Pettway, Y. D., Saunders, ..., Feng, F., ... & Brissova, M. (2024). Heterogeneous endocrine cell composition defines human islet functional phenotypes. (under review by Nature Communications)
  • Varshney, A., Manickam, N., Orchard, P., Tovar, ..., Feng, F., ... & Parker, S. C. (2024). Population-scale skeletal muscle single-nucleus multi-omic profiling reveals extensive context specific genetic regulation. bioRxiv.
  • Feng, F., Moran, S. P., & Liu, J. (2024). Quagga: a stripe caller for chromatin contact maps (under review by Genome Research)

学术报告

  • "Defining human pancreatic cell composition and spatial distribution with machine learning methods", AI in Precision Medicine of Diabetes and Other Chronic Diseases Workshop, 美国 罗克韦尔, 2024/10
  • "Application of knowledge graphs in biomedical fields", CCHC Omics Seminar, 美国 纳什维尔, 2024/10
  • "GenomicKB: a knowledge graph for human genome", Intellectual Systems of Molecular Biology (ISMB), 法国 里昂, 2023/7
  • "A generalizable framework to comprehensively predict epigenome, chromatin organization, and transcriptome", Great Lakes Bioinformatics (GLBIO) conference, 加拿大 蒙特利尔, 2023/5
  • "An overview of Hi-C downstream analysis", Chromatin 3D Folding Workshop, 美国 休斯顿 得克萨斯大学休斯顿健康中心, 2023/3
  • "GenomicKB: a knowledge graph for human genome", Tools and Technology Seminar, 美国 安娜堡 密歇根大学, 2023/1
  • "Connecting high-resolution 3D chromatin organization with epigenomics", Intellectual Systems of Molecular Biology (ISMB), 美国 麦迪逊, 2022/7
  • "An accurate and interpretable model for predicting high-resolution 3D chromatin organization", 4DN Consortium Joint Analysis Working Group, 云端会议 2019/9

教学经历

  • 研究生助教/讲师, BIOINF 593/EECS 598 计算生物学中的机器学习算法 (Machine Learning in Computational Biology), 密歇根大学, 2022秋季学期

审稿经历

  • 期刊审稿人（Co-reviewer）, Nature Metabolism
  • 期刊审稿人（Co-reviewer）, Nature Communications
  • 期刊审稿人, PLoS Computational Biology
  • 会议审稿人, Conference on Neural Information Processing Systems (NeurIPS) AI4Science Workshop
  • 会议审稿人, International Conference on Machine Learning (ICML) AI4Science Workshop
  • 会议审稿人, International Conference on Machine Learning (ICML) Generative AI and Biology (GenBio) Workshop

获奖情况

  • Data Resource Trainee Scholar Award, Integrated Islet Distribution Program (IIDP), 2025
  • AI Workshop Young Scholar Travel Award, National Institute of Diabetes and Digestive and Kidney Disease (NIDDK), 2024
  • Rackham Conference Travel Award, University of Michigan, 2022 and 2023
  • Program in Biomedical Sciences Fellowship, University of Michigan, 2019
  • 北京大学优秀毕业生/化学与分子工程学院优秀毕业生, 2018
  • 中国化学奥林匹克竞赛决赛金牌 (前100名), 2013