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Nabil Mohammed

Nabil Mohammed

PhD Rotation Student

Developing methods to uncover genetics of complex traits.

Statistical genetics Functional genomics Drug discovery Precision medicine

Nabil Mohammed is a graduate student in the UCLA Bioinformatics Interdepartmental Program and worked with Dr. Yosuke Tanigawa at the intersection of statistical genetics and data science. His research focused on developing and applying statistical models for large-scale genomic data, with an emphasis on genetic risk prediction and translational genomics. Prior to UCLA, he worked as a computational biologist at Octant, where he supported small-molecule drug discovery for rare disease. He earned his B.S. in Bioinformatics from UC Santa Cruz, where he gained his first exposure to research with hands-on wet-lab and computational projects. Outside of lab, he enjoys spending time running, cycling, and hiking.

Posts and Publications

Dissecting Alzheimer's disease heterogeneity by cross-trait polygenic prediction

Led by Bill Li, this work introduces cross-trait polygenic prediction as a strategy for using phenome-wide PGS libraries in deeply phenotyped cohorts to reveal multiple polygenic …

Spring 2026 social at TukTuk Thai

Tanigawa Lab Spring 2026 social

We had a social gathering to celebrate the near completion of the Spring 2026 quarter.

Nabil Mohammed
Nabil Mohammed
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