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Your Environment. Your Health.

YuanYuan Li, Ph.D.

Biostatistics & Computational Biology Branch

YuanYuan Li
Yuanyuan Li, Ph.D.
Fellow — IRTA
Tel 984-287-3838
111 T W Alexander Dr
Rall Building
Research Triangle Park, NC 27709

Research Summary

Yuanyuan Li, Ph.D., has joined NIEHS in May 2011, and is currently an IRTA postdoc fellow under the supervision of Leping Li, Ph.D. Her primary research interest is in computational genomics especially next-gen sequencing analysis. Li obtained a Ph.D. in computer science in 2010 from the University of Tennessee, Knoxville. Her other research interests including clustering, Markov models, detection, decision theories, network analysis and big data.

Computational Genomics

  • Characterization of constitutive CTCF: Recent studies suggested that human/mammalian genomes are divided into large, discrete domains that are units of chromosome organization. CTCF, a CCCTC binding factor, has a diverse role in genome regulation including transcriptional regulation, chromosome-boundary insulation, DNA replication, and chromatin packaging. It remains unclear whether a subset of CTCF binding sites plays a functional role in establishing/maintaining chromatin topological domains. Our results suggest that the constitutive CTCF sites may play a role in organizing/maintaining the recently identified topological domains that are common across most human cells.
  • Method for analyzing genome-wide protein binding patterns from ChIP-seq data: A protein may bind to its target DNA sites constitutively, i.e., regardless of cell type. Intuitively, constitutive binding sites should be biologically functional. Knowing the locations of all constitutive sites for a protein of interest is prerequisite for understanding these sites’ functional relevance. Robust and efficient computational methods for identifying constitutive binding sites are lacking, however. Li and her colleagues propose a method, T-KDE, to identify the locations of constitutive binding sites. T-KDE, which combines a binary range tree with a kernel density estimator, is applied to ChIP-seq data from multiple cell lines. Besides constitutive binding sites for a given TF, T-KDE can identify genomic “hot spots” where several different proteins bind and, conversely, cell-specific sites bound by a given protein.


  • T-KDE: T-KDE will identify the locations of constitutive binding sites. T-KDE, which combines a binary range tree with a kernel density estimator, is applied to ChIP-seq data from multiple cell lines.

Selected Publications

  1. Li Y, Umbach DM, Li L. T-KDE: a method for genome-wide identification of constitutive protein binding sites from multiple ChIP-seq data sets. BMC genomics 2014 15:27 [Abstract]
  2. LY., Huang, W., Niu, L., Covo, S., Umbach, D.M., and Li, L. Characterization of constitutive CTCF/Cohesin loci: a possible role in establishing topological domains in mammalian genomes. BMC Genomics, 2013, 14:553 doi:10.1186/1471-2164-14-553.
  3. S. Lenaghan, Y. Li (co-first author), H. Zhang, J. Burris, C. Stewart, L. E. Parker, and M. Zhang, Monitoring the Environmental Impact of TiO2 Nanoparticles Using a Plant-based Sensor-network, IEEE Transactions on Nanotechnology, 2013, PP(99). doi: 10.1109/TNANO.2013.2242089.
  4. Y. Li, S. Lenaghan, and Mingjun Zhang. A Data-driven Predictive Approach for Drug Delivery Using Machine Learning Techniques, PLoS ONE, 2012, 7(2): e31724. doi:10.1371/journal.pone.0031724.
  5. Y. Li and L. E. Parker, Nearest Neighbor Imputation Using Spatial-Temporal Correlations in Wireless Sensor Networks, Information Fusion, 2012, ISSN 1566-2535,
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