Jeff Longmate
Papers
1
Total Citations
55
H-Index
1
About
Jeff Longmate is a biostatistician whose research has significantly advanced the understanding of genetic mutations in cancer, particularly through the lens of statistical genetics and clinical trial design. His most-cited work, a 2003 study on ATM missense mutations in breast cancer patients, has garnered 55 citations and remains a foundational reference in the field. This paper contributed to the critical insight that ATM mutations, previously linked to ataxia-telangiectasia, may also play a role in sporadic breast cancer risk, influencing subsequent genetic screening and risk assessment strategies. Longmate's broader contributions include developing statistical methods for analyzing high-dimensional genomic data and designing efficient clinical trials for cancer therapies. His work often bridges the gap between complex biological data and actionable clinical insights, helping researchers identify meaningful genetic variants amidst noise. With a career focused on collaborative, data-driven approaches, Longmate has been instrumental in shaping how statisticians and oncologists interpret mutation prevalence and its implications for patient outcomes. His research continues to inform precision medicine efforts, making him a key figure in the intersection of biostatistics and cancer genomics.
Research Focus
Key Achievements
Top Papers
- 1ATM missense mutations are frequent inpatients with breast cancer55 citations · 2003