Rate My Professor Yosuke Tanigawa

Tanigawa's research lies at the intersection of statistical genetics and computational biology, focusing on developing computational and statistical methods to dissect disease heterogeneity. His academic interests encompass disease heterogeneity dissection, statistical genetics and polygenic score methods, biomedical data science and multimodal integration, AI/ML methods for genomic and clinical data, and translational applications in precision medicine. He has earned major awards including the JST PRESTO award from the Japan Science and Technology Agency in 2025, AJHG Trainee Publication Award in 2024, MIT Technology Review’s Innovators Under 35 Japan in 2022, and ASHG Charles J. Epstein Trainee Award Winner in 2022. Key publications include "Hypometric genetics: Improved power in genetic discovery by incorporating quality control flags" (American Journal of Human Genetics, 2024), "A polygenic score method boosted by non-additive models" (Nature Communications, 2024), "Power of inclusion: Enhancing polygenic prediction with admixed individuals" (American Journal of Human Genetics, 2023), "Human microglial state dynamics in Alzheimer’s disease progression" (Cell, 2023), and "Genetics of 35 blood and urine biomarkers in the UK Biobank" (Nature Genetics, 2021). His work, cited over 6,000 times, has advanced genomic analysis and precision medicine.