Jingyi Jessica Li

The PI, Associate Professor in Statistics

Wang, Y.X.R., Li, L., Li, J.J., and Huang, H. (2020). Network modeling in biology: statistical methods for gene and brain networks. Statistical Science (in press).

Jiang, R.Li, W.V., and Li, J.J. (2020). mbImpute: an accurate and robust imputation method for microbiome data. bioRxiv[ SOFTWARE ]

Li, W.V.*, Li, S.*, Tong, X., Deng, L., Shi, H., and Li, J.J. (2019). AIDE: annotation-assisted isoform discovery with high precision. Genome Research 29:2056-2072. [ SOFTWARE ] [ COVER ART ] [ UCLA News ]

Li, J.J., Chew, G.-L., and Biggin, M.D. (2019). Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes. Genome Biology 20:162. [ CODE ]

Li, W.V. and Li, J.J. (2019). A statistical simulator scDesign for rational scRNA-seq experimental design. Bioinformatics 35(14):i41–i50. [ ISMB/ECCB 2019 ] [ SOFTWARE ]

Ge, X.*, Zhang, H.*, Xie, L., Li, W.V., Kwon, S.B., and Li, J.J. (2019). EpiAlign: an alignment-based bioinformatic tool for comparing chromatin state sequences. Nucleic Acids Research gkz287. [ SOFTWARE ] [ WEBSITE ]

Razaee, Z.S., Amini, A.A., and Li, J.J. (2019). Matched bipartite block model with covariates. Journal of Machine Learning Research 20:1-44.

Duong, D., Ahmad, W.U., Eskin, E., Chang, K.-W., and Li, J.J. (2019). Word and sentence embedding tools to measure semantic similarity of Gene Ontology terms by their definitions. Journal of Computational Biology 26(1):38-52. [ SOFTWARE ]

Li, W.V. and Li, J.J. (2018). Modeling and analysis of RNA-seq data: a review from a statistical perspective. Quantitative Biology 6(3):195-209.

Burke, J.E., Longhurst, A.D., Merkurjev, D., Sales-Lee, J., Rao, B., Moresco, J.J., Yates III, J.R., Li, J.J., and Madhani, H.D. (2018). Spliceosome profiling visualizes operations of a dynamic RNP at nucleotide resolution. Cell 173(4):1014–1030.e17.

Li, W.V.*, Zhao, A., Zhang, S., and Li, J.J.* (2018). MSIQ: joint modeling of multiple RNA-seq samples for accurate isoform quantification. Annals of Applied Statistics 12(1):510-539. [ SOFTWARE ] [ COLOR PDF ]

Jonassaint, C.R., Kang, C., Abrams, D.M., Li, J.J.Mao, J.Jia, Y., Long, Q., Sanger, M., Jonassaint, J.C., De Castro, L., and Shah, N. (2017). Understanding patterns and correlates of daily pain using the sickle cell disease mobile application to record symptoms via technology (SMART). British Journal of Haematology.

Clifton, S.M., Kang, C.Li, J.J., Long, Q., Shah, N., and Abrams, D.M. (2017). Hybrid statistical and mechanistic mathematical model guides mobile health intervention for chronic pain. Journal of Computational Biology 24(7):675-688.

Li, W.V.Chen, Y., and Li, J.J. (2017). TROM: a testing-based method for finding transcriptomic similarity of biological samples. Statistics in Biosciences 9(1):105-136. [ SOFTWARE ]

Yang, Y.*, Yang, Y.T.*, Yuan, J., Lu, Z.J., and Li, J.J. (2017). Large-scale mapping of mammalian transcriptomes identifies conserved genes associated with different cell states. Nucleic Acids Research 45(4):1657-1672. [ DATA ]

Li, J.J. and Tong, X. (2016). Genomic applications of the Neyman–Pearson classification paradigm. Big Data Analytics in Genomics. Springer (New York).

Li, W.V.Razaee, Z.S., and Li, J.J. (2016). Epigenome overlap measure (EPOM) for comparing tissue/cell types based on chromatin states. BMC Genomics 17(Supp 1):10. [ SOFTWARE ]

Li, J.J., Huang, H., Qian, M., and Zhang, X. (2015). Chapter 24: Transcriptome analysis using next-generation sequencing. Advanced Medical Statistics (2nd Edition).

Liu, Z., Dai, S., Bones, J., Ray, S., Cha, S., Karger, B. L., Li, J.J., Wilson, L., Hinckle, G., and Rossomando, A. (2015). A quantitative proteomic analysis of cellular responses to high glucose media in Chinese hamster ovary cells. Biotechnology Progress 31(4):1026-38.

Li, J.J. and Biggin, M.D. (2015). Statistics requantitates the central dogma. Science 347(6226):1066-1067. [ UCLA News ] [ Interview at Significance 12(3):8 ]

Gerstein, M.B.*, Rozowsky, J.*, Yan, K.K.*, Wang, D.*, Cheng, C.*, Brown, J.B.*, Davis, C.A.*, Hillier, L*, Sisu, C.*, Li, J.J.*, Pei, B.*, Harmanci, A.O.*, Duff, M.O.*, Djebali, S.*, and 82 other authors from the modENCODE consortium (2014). Comparative analysis of the transcriptome across distant species. Nature 512(7515):445-448. [ NIH news ]

Boyle, A., Araya, C., Brdlik, C., Cayting, P., Cheng, C., Cheng, Y., Gardner, K., Hillier, L., Janette, J., Jiang, L., Kasper, D., Kawli, T., Kheradpour, P., Kundaje, A., Li, J.J., and 25 other authors from the modENCODE and ENCODE consortia (2014). Comparative analysis of regulatory information and circuits across distant species. Nature 512(7515):453-456. [ NIH news ]

Fisher, W.W., Li, J.J., Hammonds, A.S., Brown, J.B., Pfeiffer, B., Weiszmann, R., MacArthur, S., Thomas, S., Stamatoyannopoulos, J.A., Eisen, M.B., Bickel, P.B., Biggin, M.D., and Celniker, S.E. (2012). DNA regions bound at low occupancy by transcription factors do not drive patterned reporter gene expression in Drosophila. Proc Natl Acad Sci. USA 109(52):21330–21335.

Gao, Q., Ho, C., Jia, Y., Li, J.J., and Huang, H. (2012). Biclustering of linear patterns in gene expression data (CLiP). Journal of Computational Biology 19(6):619-631.

Li, J., Li, J., and Chen, B. (2012). Oct4 was a novel target of Wnt signaling pathway. Molecular and Cellular Biochemistry 362:233–240.

Li, J.J., Jiang, C.-R., Brown, B.J., Huang, H., and Bickel, P.J. (2011). Sparse linear modeling of RNA-seq data for isoform discovery and abundance estimation. Proc Natl Acad Sci. USA 108(50):19867-19872. [ SOFTWARE ]

MacArthur, S.*, Li, X.Y.*, Li, J.*, Brown, J.B., Chu, H.C., Zeng, L., Grondona, B.P., Hechmer, A., Simirenko, L., Keranen, S.V., Knowles, D.W., Stapleton, M., Bickel, P., Biggin, M.D., and Eisen, M.B. (2009). Developmental roles of 21 Drosophila transcription factors are determined by quantitative differences in binding to an overlapping set of thousands of genomic regions. Genome Biology 10:R80. [ Faculty of 1000 recommendation ]