James Lindsay
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Associate Director: Knowledge Systems Group
Also affiliated: Boston University (2020–2022); Northwestern University (1989); Fairfield University (2014); Brigham and Women's Hospital (2024); National Agricultural Statistics Service (2021); Agricultural Research Service (2021); DuPont (United States) (1989); Harvard University (2021–2025); University of Connecticut (2011–2016); University of Leicester (2009); King's College London (2025); Barts Health NHS Trust (2021); California Pacific Medical Center (1995); Cambridge University Hospitals NHS Foundation Trust (2013); Forth Valley Royal Hospital (2014–2018); Worcestershire Royal Hospital (2015); Dana-Farber Cancer Institute (2016–2025); Cancer Clinic (2021); Dana-Farber/Harvard Cancer Center (2025); Dana-Farber Brigham Cancer Center (2023–2024)
Faculty Researcher
Research Areas
Biomedical Subjects
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Biography and Research Information
OverviewAI-generated summary
James Lindsay's research focuses on the analysis and visualization of genomic and clinical data, particularly in the context of non-small cell lung cancers (NSCLC). He has investigated the association of high tumor mutation burden with immune infiltration and clinical outcomes in NSCLC patients undergoing PD-L1 blockade. His work also explores the clinicopathologic characteristics and outcomes related to specific genomic alterations, such as those in the SWItch/Sucrose NonFermentable (SWI/SNF) family, within NSCLC and their response to immune checkpoint inhibition.
Lindsay has contributed to large-scale data initiatives like the AACR Project GENIE, which aims to compile genomic and clinical data from a substantial number of cancer cases. His publications include analyses of longitudinal genomic and clinical data from this project, as well as studies dissecting the correlates of specific mutations, such as KRASG12D, in NSCLC. His research also extends to understanding immune determinants of CAR-T cell expansion in solid tumor patients and investigating treatment strategies involving combined PD-L1 and CTLA-4 inhibition with radiation for metastatic colorectal cancer.
With an h-index of 23 and over 5,000 citations across 460 publications, Lindsay is recognized as a highly cited researcher. He is an Associate Director for the Knowledge Systems Group at the University of Arkansas at Fayetteville and maintains an active lab website.
Metrics
- h-index: 23
- Publications: 460
- Citations: 5,102
Selected Publications
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Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models (2025)
Collaboration Network
Top Collaborators
- Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models
- Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models
- Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models
- Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models
- Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models
- Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models
- Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models
- Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models
- Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models
- Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models
- Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models
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