Zoe Li Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Researcher

National Center for Toxicological Research

faculty

12 h-index 39 pubs 463 cited

Research Areas

Advanced Neural Network Applications Pharmacological Effects and Toxicity Studies Hydrology and Watershed Management Studies Medical Imaging Techniques and Applications Computational Drug Discovery Methods Ecology and Vegetation Dynamics Studies Meta-analysis and systematic reviews

Links

ORCID

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OverviewAI-generated summary

Zoe Li's research focuses on the application of machine learning and deep learning techniques across various scientific domains. Recent work includes developing models for toxicity prediction, segmenting brain tumor MRI images, and fingerprinting protein-ligand interactions for drug discovery. Li has also investigated the impacts of environmental systems on hydrological processes, particularly in river basins in southwestern China, examining changes in vegetation cover and runoff under climate change. Further research explores the dynamic resilience of hydropower infrastructure in multihazard environments and dam system operational safety. Li collaborates with Tucker A. Patterson, Fan Dong, Wenjing Guo, and Minjun Chen, all from the National Center for Toxicological Research, with whom they have co-authored numerous publications.

Metrics

  • h-index: 12
  • Publications: 39
  • Citations: 463

Selected Publications

  • Developing predictive models for µ opioid receptor binding using machine learning and deep learning techniques (2025) DOI
  • Computational Toxicology (2024) DOI
  • Decoding the κ Opioid Receptor (KOR): Advancements in Structural Understanding and Implications for Opioid Analgesic Development (2024) DOI
  • Fingerprinting Interactions between Proteins and Ligands for Facilitating Machine Learning in Drug Discovery (2024) DOI
  • Machine learning and deep learning for brain tumor MRI image segmentation (2023) DOI
  • Review of machine learning and deep learning models for toxicity prediction (2023) DOI
  • Developing a SARS-CoV-2 main protease binding prediction random forest model for drug repurposing for COVID-19 treatment (2023) DOI
  • QSAR models for predicting in vivo reproductive toxicity (2023) DOI
  • EADB—A database providing curated data for developing QSAR models to facilitate the assessment of endocrine activity (2023) DOI
  • Decision forest—a machine learning algorithm for QSAR modeling (2023) DOI
  • Three-Dimensional Structural Insights Have Revealed the Distinct Binding Interactions of Agonists, Partial Agonists, and Antagonists with the µ Opioid Receptor (2023) DOI

Collaborators

Researchers in the database who share publications

Tucker A. Patterson National Center for Toxicological Research 12 shared publications Fan Dong National Center for Toxicological Research 10 shared publications Wenjing Guo National Center for Toxicological Research 3 shared publications Minjun Chen National Center for Toxicological Research 2 shared publications Weigong Ge National Center for Toxicological Research 2 shared publications Wen Zou National Center for Toxicological Research 1 shared publication Ann Varghese National Center for Toxicological Research 1 shared publication

Similar Researchers

Based on overlapping research topics

Daniel Irabor University of Arkansas at Pine Bluff
Advanced Neural Network Applications Pharmacological Effects and Toxicity Studies Medical Imaging Techniques and Applications
Good match 4 shared topics
Tucker A. Patterson National Center for Toxicological Research
Advanced Neural Network Applications Pharmacological Effects and Toxicity Studies Medical Imaging Techniques and Applications
Good match 5 shared topics
Fan Dong National Center for Toxicological Research
Advanced Neural Network Applications Pharmacological Effects and Toxicity Studies Medical Imaging Techniques and Applications
Good match 4 shared topics
Nicole Kleinstreuer National Center for Toxicological Research
Advanced Neural Network Applications Pharmacological Effects and Toxicity Studies Computational Drug Discovery Methods
Good match 4 shared topics
Sanjay Muttineni University of Arkansas for Medical Sciences
Advanced Neural Network Applications Pharmacological Effects and Toxicity Studies Computational Drug Discovery Methods
Good match 3 shared topics
Aqiang Guo University of Arkansas at Fayetteville
Advanced Neural Network Applications Medical Imaging Techniques and Applications Computational Drug Discovery Methods
Good match 3 shared topics