Natarajan Ganesan
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Assistant Professor and Assistant Director of Research
Also affiliated: Georgetown University (2005–2011); University of Madras (1999); Alabama College of Osteopathic Medicine (2026); Georgetown University Medical Center (2006–2011); University of Saint Mary (2008); OMV Petrom (Romania) (2023–2026); New York Institute of Technology (2025–2026); Phoenix (United States) (2020); Arkansas Biosciences Institute (2025–2026)
Faculty Researcher
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Natarajan Ganesan's research interests encompass bioinformatics, genomics, and personalized medicine, with an earlier focus on cancer research and therapeutics. His work has involved developing web-based interfaces for bioscience researchers and managing public databases at the National Institutes of Health (NIH).
Dr. Ganesan has experience collaborating with researchers across academia, pharmaceutical, and biotechnology sectors. His projects have explored diverse areas, including wireless biosensors and the linguistic fingerprinting of peptide sequences. He has also contributed to business strategies and market analysis reports for healthcare organizations and international companies. His expertise has been recognized through invitations to review grant proposals for the Department of Defense and the Fulbright program.
His recent publications include work on artificial intelligence in medical education, a web application for ovarian cancer patient data integration, and studies addressing bias in public health information chatbots. Further publications explore the genomic profiles of glioblastoma and the structure-activity relationships of platinum compounds against carcinoma cell lines. He has also utilized graph neural networks for meta-analysis of transcriptomic data in lung cancer and tuberculosis research.
Metrics
- h-index: 9
- Publications: 39
- Citations: 318
Selected Publications
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Abstract 4193: Heterogeneous graph neural network meta-analysis of lung cancer and tuberculosis transcriptomic datasets reveals convergent host response networks (2026)
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Abstract 7283: Genomic landscape of IDH-wild-type glioblastoma in a patient treated with TNF-alpha inhibitor: Implications for risk stratification and therapeutic decision-making (2026)
Collaboration Network
Top Collaborators
- Abstract 7283: Genomic landscape of IDH-wild-type glioblastoma in a patient treated with TNF-alpha inhibitor: Implications for risk stratification and therapeutic decision-making
- Abstract 4193: Heterogeneous graph neural network meta-analysis of lung cancer and tuberculosis transcriptomic datasets reveals convergent host response networks
- Abstract 4193: Heterogeneous graph neural network meta-analysis of lung cancer and tuberculosis transcriptomic datasets reveals convergent host response networks
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