Kexin is a Ph.D. student in the Department of Statistics at UCLA. She got her B.S. from the Department of Mathematical Sciences at Tsinghua University, with a specialization in Probability and Statistics. Her research interest involves developing statistical methods to address scientific problems in biology. Kexin is currently working with Ya Cui on refining statistical model in detecting chromatin accessibility QTL. She is also conducting analysis on the conservation of gene function across species.
78. Chen, Y.E.*, Ge, X.*, Woyshner, K.*, McDermott, M.*, Manousopoulou, A., Ficarro, S., Marto, J., Kexin Li, Wang, L.D., and Li, J.J. (2024). APIR: a universal FDR-control framework for boosting peptide identification power by aggregating multiple proteomics database search algorithms. Genomics, Proteomics & Bioinformatics (accepted). [ SOFTWARE ] [ CODE ]
Song, D.*, Li, K.*, Ge, X., and Li, J.J. (2023). ClusterDE: a post-clustering differential expression (DE) method robust to false-positive inflation caused by double dipping. bioRxiv. [ SOFTWARE ]
53. Song, D.*, Li, K.*, Hemminger, Z., Wollman, R., and Li, J.J. (2021). scPNMF: sparse gene encoding of single cells to facilitate gene selection for targeted gene profiling. Bioinformatics 37(Supplement_1):i358–i366. [ ISMB/ECCB 2021 ] [ SOFTWARE ]
