Research Interests
Yinqing Li has a longstanding interest in developing technologies for better diagnosis and management of complex diseases. In particular, his research focuses on methods for identifying key molecular and cell players in the development of diseases and methods for gene and cell editing. Specific approaches include: single cell multi-omics spanning epigenetics, transcriptome, and signaling pathway profiling, discovery of novel genome and epigenome editing tools, and statistical inference and machine learning algorithms for high throughput data mining and processing.
Honors and awards
2019 MIT Technology Review, 35 under 35, China
2016 Extraordinary Potential Prize of 2016 Chinese Government Award for Students Abroad
2016 Wenner-Gren Fellowship
2013 McGovern Institute Fellowship
Selected Publications
1. Li Y, Lopez-Huerta VG, Adiconis X, Levandowski K, Choi S, Simmons SK, Arias-Garcia MA, Guo B, Yao AY, Blosser TR, Wimmer RD, Aida T, Atamian A, Naik T, Sun X, Bi D, Malhotra D, Hession CC, Shema R, Gomes M, Li T, Hwang E, Krol A, Kowalczyk M, Peça J, Pan G, Halassa MM, Levin JZ, Fu Z, Feng G. Distinct subnetworks of the thalamic reticular nucleus. Nature. 2020, 583(7818):819-824.
2. Habib N*, Li Y*, Heidenreich M, Swiech L, Avraham-Davidi I, Trombetta JJ, Hession C, Zhang F, Regev A. Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons. SCIENCE. 2016, 353(6302):925-8.
3. Li Y*, Jiang Y*, Chen H*, Liao W, Li Z, Weiss R, Xie Z. Modular construction of mammalian gene circuits using TALE transcriptional repressors. NATURE CHEMICAL BIOLOGY. 2015, 11(3):207-13.
