Papers

5

Total Citations

181

H-Index

4

About

Timothy D. Veenstra is a prominent researcher whose work sits at the intersection of proteomics, mass spectrometry, and cancer biomarker discovery. His research has made significant contributions to the development of high-throughput analytical techniques for proteome analysis and their clinical application in disease diagnosis. Veenstra's most impactful contribution comes from his work on serum proteomic profiling for prostate cancer detection, which garnered 114 citations and demonstrated that artificial intelligence-driven pattern recognition could analyze complex proteomic data to discriminate prostate cancer from benign prostates in patients with ambiguous PSA levels — a critical diagnostic challenge in urology. This work exemplifies his commitment to translating advanced proteomics into clinically meaningful tools. On the methodological front, Veenstra pioneered two-dimensional electrophoretic and chromatographic separation strategies coupled with electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry, advancing the capacity for high-throughput proteome analysis. His development of Pooled ORF Expression Technology (POET) further demonstrated his innovative approach to identifying proteins amenable to high-yield expression, while his contributions to peptide array synthesis helped accelerate protein kinase characterization. Across his body of work, Veenstra has consistently pushed the boundaries of proteomic methodology and its biomedical applications.

Research Focus

Key Achievements

4
H-Index
5
Papers
181
Total Citations
36
Avg Citations/Paper
🏆 Most Cited Paper
SERUM PROTEOMIC PROFILING CAN DISCRIMINATE PROSTATE CANCER FROM BENIGN PROSTATES IN MEN WITH TOTAL PROSTATE SPECIFIC ANTIGEN LEVELS BETWEEN 2.5 AND 15.0 NG/ML
114 citations · 2004
📈 Most Prolific Year: 2000 (2 Papers)
🤝 Key Collaborators: 32
🏛 Institutions: Louisiana State University, Pacific Northwest National Laboratory, National Cancer Institute, National Institutes of Health

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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