Yanjun Li

Yanjun Li, Ph.D.

Assistant Professor

Department: Medicinal Chemistry
Business Phone: (352) 273-9957
Business Email: yanjun.li@ufl.edu

About Yanjun Li

Yanjun Li is an Assistant Professor (AI Initiative) in the Department of Medicinal Chemistry at the College of Pharmacy, University of Florida. His research interests span the fields of deep learning, drug discovery, and precision medicine, with a particular emphasis on AI-driven drug discovery. Dr. Li’s work aims to develop innovative AI algorithms to tackle foundational life science challenges with broad scientific impacts and to optimize and automate real-world drug discovery and design pipelines.

Dr. Li earned his Ph.D. in computer science from the University of Florida and then worked as a Senior Research Scientist at the Institute of Deep Learning, Baidu Research USA in Sunnyvale, California. His passion for real-world drug discovery led him to join Calico Life Sciences, an Alphabet-founded research and development lab for human aging research, as a Machine Learning Scientist. In 2023, Dr. Li started his tenure-track Assistant Professorship in the Department of Medicinal Chemistry at the University of Florida, where he continues to pursue cutting-edge research in AI-driven drug discovery.

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Teaching Profile

Courses Taught
2024-2025
PHA6467C Drug Design II
2024
PHA7979 Advanced Research
2024
PHA6910 Supervised Research

Research Profile

Dr. Li’s research focuses on AI-driven drug discovery and optimization, utilizing deep learning techniques to accelerate the discovery of novel functional molecules for improved human health outcomes. His current research interests include: (1) developing deep learning algorithms for the design of small molecules, peptides, antibodies, and domain proteins to expedite the drug design pipeline and lead to potential drug candidates; (2) predicting molecular interactions through domain-tailored deep learning methods and molecular dynamics simulations; (3) exploring molecular structure-property relationships to guide the structure-based drug design and optimization; (4) analyzing multi-omics data, electronic health records, and medical imaging data for drug repurposing and synergistic combinations with machine learning methods; (5) advancing the capacity of machines to understand the intricate language of chemistry with natural language processing.

Dr. Li’s laboratory fosters a culture of interdisciplinary and translational collaboration to cultivate a dynamic and distinctive working environment. The lab endeavors to advance the frontiers of AI-driven drug discovery while propelling the field of artificial intelligence towards real-world applications in the life sciences.

Open Researcher and Contributor ID (ORCID)

0000-0002-6277-4189

Publications

2024
Analysis and Visualization of Single-Cell Sequencing Data with Scanpy and MetaCell: A Tutorial
Methods in Molecular Biology. 383-445 [DOI] 10.1007/978-1-0716-3642-8_17.
2024
Extracellular vesicles for developing targeted hearing loss therapy
Journal of Controlled Release. 366:460-478 [DOI] 10.1016/j.jconrel.2023.12.050.
2024
Identifying acute illness phenotypes via deep temporal interpolation and clustering network on physiologic signatures
Scientific Reports. 14(1) [DOI] 10.1038/s41598-024-59047-x. [PMID] 38600110.
2024
Morphological profiling for drug discovery in the era of deep learning
Briefings in Bioinformatics. 25(4) [DOI] 10.1093/bib/bbae284. [PMID] 38886164.
2023
BatmanNet: bi-branch masked graph transformer autoencoder for molecular representation.
Briefings in bioinformatics. 25(1) [DOI] 10.1093/bib/bbad400. [PMID] 38033291.
2022
Analysis and Visualization of Spatial Transcriptomic Data
Frontiers in Genetics. 12 [DOI] 10.3389/fgene.2021.785290. [PMID] 35154244.
2022
Deep Learning in Drug Design: Protein-Ligand Binding Affinity Prediction
IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(1):407-417 [DOI] 10.1109/tcbb.2020.3046945.
2022
DyScore: A Boosting Scoring Method with Dynamic Properties for Identifying True Binders and Nonbinders in Structure-Based Drug Discovery
Journal of Chemical Information and Modeling. 62(22):5550-5567 [DOI] 10.1021/acs.jcim.2c00926. [PMID] 36327102.
2022
Physiologic signatures within six hours of hospitalization identify acute illness phenotypes
PLOS Digital Health. 1(10) [DOI] 10.1371/journal.pdig.0000110. [PMID] 36590701.
2021
Reinforcement learning in surgery
Surgery. 170(1):329-332 [DOI] 10.1016/j.surg.2020.11.040. [PMID] 33436272.
2020
Decision analysis and reinforcement learning in surgical decision-making
Surgery. 168(2):253-266 [DOI] 10.1016/j.surg.2020.04.049. [PMID] 32540036.
2019
Author Correction: Predicting the clinical impact of human mutation with deep neural networks
Nature Genetics. 51(2):364-364 [DOI] 10.1038/s41588-018-0329-z.
2019
DeepAtom: A Framework for Protein-Ligand Binding Affinity Prediction
2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). [DOI] 10.1109/bibm47256.2019.8982964.
2018
Predicting the clinical impact of human mutation with deep neural networks
Nature Genetics. 50(8):1161-1170 [DOI] 10.1038/s41588-018-0167-z. [PMID] 30038395.

Grants

Jun 2024 ACTIVE
Enhancing Cancer Diagnosis and Treatment through Innovative Glycan- Specific Protein Engineering
Role: Co-Investigator
Funding: FL DEPT OF HLTH
Dec 2023 ACTIVE
ExoTarget Platform as a programmable delivery system
Role: Co-Investigator
Funding: NATL INST OF HLTH
Jun 2023 ACTIVE
UF Health Cancer Center Support Grant
Role: Project Manager
Funding: NATL INST OF HLTH NCI

Education

Ph.D. (Computer Science)
2021 · University of Florida
M.S. (Communication and Information System)
2015 · University of Electronic Science and Technology of China
M.S. (Information, Production and Systems Engineering)
2015 · Waseda University
B.S. (Information Engineering)
2012 · University of Electronic Science and Technology of China

Contact Details

Phones:
Business:
(352) 273-9957
Emails:
Business:
yanjun.li@ufl.edu
Addresses:
Business Mailing:
PO Box 100485
1345 CENTER DR
GAINESVILLE FL 32610
Business Street:
1345 CENTER DR
MSB P6-33
GAINESVILLE FL 32610