Nathan Abell
Computational Geneticist
Berkeley, California, United States
Summary
👤
Senior🎓
Top SchoolNathan Abell is a computational geneticist based in Berkeley with 11 years' experience applying computational, experimental, and statistical genomics to precision medicine and drug design. He combines a PhD in Genetics and an MS in Statistics from Stanford with dual undergraduate degrees in Cellular & Molecular Biology and Plan II Honors, giving him a rare mix of quantitative, wet-lab, and humanities training. At Octant he translates genomic signals into actionable insights for therapeutic programs, while consulting on bioinformatics at UT Austin's Xhemalce Lab. His background spans deep research in academic labs (Stanford Montgomery Lab) and hands-on assay development, enabling him to bridge hypothesis-driven science and scalable computational pipelines. Colleagues know him for turning complex genetic datasets into interpretable models that directly inform target selection and experimental design.
11 years of coding experience
10 years of employment as a software developer
B.A., Plan II Honors, Political Science, Philosophy, B.A., Plan II Honors, Political Science, Philosophy at The University of Texas at AustinPh.D., Genetics, Ph.D., Genetics at Stanford University School of MedicineM.S., Statistics, M.S., Statistics at Stanford UniversityProgramming languages (1)
Github contributions (5)
nsabell/nsabell.github.io
Dec 2017 - Jan 2025
Contributions:4 PRs, 100 pushes, 2 branches in 7 years 2 months
nsabell/mpra-v2
Jul 2019 - Jun 2021
Contributions:1 release, 43 commits, 69 pushes in 1 year 11 months
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