Leping Li
Biostatistics & Computational Biology
Institut Pasteur de Bangui
Mauritius
Biography
Leping Li, Ph.D., is Acting Deputy Branch Chief and a principal investigator in the Biostatistics and Computational Biology Branch. Li and his staff are developing and implementing methods for detecting and discovering functional elements such as the cis-regulatory motifs in a set of sequences using Markov models and Expectation Maximization (EM) methods. Specifically, they developed an efficient sequence alignment algorithm for identifying conserved segments between two divergent sequences, e.g., promoter sequences. Li's group also worked on methods that improve the quality of motif models and a motif identification tool that controls the false discovery rate. Li recently developed the GADEM software that can be applied to large scale sequence data for unbiased motif discovery. Currently, his group is developing a method that identifies transcription factor and its co-regulatory motifs in ChIP-seq datasets and computational/statistical methods for identifying genomic loci that are differentially enriched in sequence reads counts in ChIP-seq and mRNA-seq data.
Research Interest
Biostatistics & Computational Biology
Publications
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Rockhill, B., Newman, B., and Weinberg, C.R. Use and misuse of population attributable fractions. American Journal of Public Health, 88(1): 15-19, 1998.
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Li Y, Krahn JM, Flake GP, Umbach DM, Li L. Toward predicting metastatic progression of melanoma based on gene expression data. Pigment cell & melanoma research 2015 28(4):453-463