Computational Biologist,
Calico Life Sciences
email: qsw[at]calicolabs.com
Twitter: @qbw_128
GitHub: @QingboWang
ORCID: 0000-0002-9110-5830
researchmap: qingbowang
google scholar
CV: Eng / JP
- 学士 (B.S.) 東京大学
(2012/04-2016/03 理学部 生物信息科学科 / 理科一類入学)
遗传统计学 / 群体遗传学 / 功能基因组学 / 非编码DNA変異 / 精彩定位 / 基因表达 ...
Wang, Q.S., Hasegawa, T., Namkoong, H. et al. Statistically and functionally fine-mapped blood eQTLs and pQTLs from 1,405 humans reveal distinct regulation patterns and disease relevance. Nat Genet (2024). https://doi.org/10.1038/s41588-024-01896-3
Wang, Q.S., Edahiro, R., Namkoong, H. et al. The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force. Nat Commun 13, 4830 (2022). https://doi.org/10.1038/s41467-022-32276-2
Wang, Q.S., Kelley, D.R., Ulirsch, J. et al. Leveraging supervised learning for functionally informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs. Nat Commun 12, 3394 (2021). https://doi.org/10.1038/s41467-021-23134-8
Wang, Q., Pierce-Hoffman, E., Cummings, B.B. et al. Landscape of multi-nucleotide variants in 125,748 human exomes and 15,708 genomes. Nat Commun 11, 2539 (2020). https://doi.org/10.1038/s41467-019-12438-5
Karczewski, K.J., Francioli, L.C., Tiao, G. Cummings, B.B., Alföldi, J., Wang, Q. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020). https://doi.org/10.1038/s41586-020-2308-7
2016/09-2021/05 The Nakajima Foundation Scholarship (Summary in Japanese)
2020/03 Finalist, MIT Sloan Sports Analytics Conference (SSAC) Hackathon (Presentation link)
2019/12 Molecular Biology Sciety of Japan (MBSJ) Early Career Researchers in Overseas Award
2019/06 Global Grand Prize, Microsoft Vivli Datathon (Manuscript, Press)
2018-2019 Harvard Brain Science Initiative (HBI) Young Scientist Development Award (Article)