Leping Li, Ph.D.

Biostatistics Branch

Leping Li, Ph.D.
Principal Investigator

Tel (919) 541-5168
Fax (919) 541-4311
li3@niehs.nih.gov

Curriculum Vitae (li-cv.pdf)   P.O. Box 12233
Mail Drop A3-03
Research Triangle Park, North Carolina 27709
Delivery Instructions

Leping Li and his staff are developing and implementing methods for detecting and discovering functional elements such as the cis-regulatory motifs in the promoter regions of genes using Markov models and Expectation Maximization (EM) methods. They are also interested in developing methods for analyzing high-dimensional data from microarray and proteomics studies. Specific areas of interests include:

• Optimized mixed Markov models for motif identification
• Accurate anchoring alignment of divergent sequences
• A method for gene set enrichment analysis for continuous non-monotone relationships
• Optimized position weight matrix (PWM) for motif detection (GAPWM)
• A genetic algorithm/k-nearest neighbor (GA/KNN) method for microarray and proteomics data analysis

The source code and documentation for GA/KNN and GAPWM may be downloaded from the Biostatistics Branch Resources page, but more information on GA/KNN appears on Li’s Studies page.

Selected Publications

1. Li, L., Darden, T.A., Weinberg, C.R., Levine, A.J. and Pedersen L.G. Gene assessment and sample classification for gene expression data using a genetic algorithm/k-nearest neighbor method. Combinatorial Chemistry and High Throughput Screening, 2001, 4, 727. [Abstract] (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=11894805&query_hl=7&itool=pubmed_DocSum)
2. Li, L., Weinberg, C.R., Darden, T.A. and Pedersen L.G. Gene selection for sample classification based on gene expression data: study of sensitivity to choice of parameters of the GA/KNN method. Bioinformatics, 2001, 17, 1131. [Download the PDF] (http://bioinformatics.oxfordjournals.org/cgi/reprint/17/12/1131)
3. Heinloth, A.N., Irwin, R.D., Boorman, G.A., Nettesheim, P., Fannin, R.D., Sieber, S.O., Snell, M.L., Tucker, C.J., Li, L., Travlos, G.S., Vansant, G., Blackshear, P.E., Tennant, R.W., Cunningham, M.L. and Paules, R.S. Gene expression profiling of rat livers reveals early indicators of potential adverse effects. Toxicol. Sci., 2004, 80, 193. [Article] (http://toxsci.oxfordjournals.org/cgi/content/full/80/1/193)
4. Liu D, Umbach DM, Peddada SD, Li L, Crockett PW, Weinberg CR.  A random-periods model for expression of cell-cycle genes. Proc Natl Acad Sci USA. 2004, 101, 7240. [Abstract](http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=15123814&query_hl=4&itool=pubmed_docsum)
5. Li, L., Umbach, D.M., Terry, P. and Taylor, J.A. Application of the GA/KNN method to SELDI proteomics data. Bioinformatics, 2004, 20, 1638. [Download the PDF] (http://bioinformatics.oxfordjournals.org/cgi/reprint/20/10/1638)
6. Zhang, D. Stumpo, D.J., Graves, J.P., DeGraff, L.M., Grissom, S.F., Collins, J.B., Li, L., Zeldin, D.C. and Blackshear, P.J. Identification of potential target genes for transcription factor RFX4_v3 in the developing mouse brain. J. Neurochem., 2006, 98, 860-875. [Abstract] (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=16893423&query_hl=2&itool=pubmed_docsum)
7. Liu, D., Peddada, S.D., Li, L. and Weinberg, C.R. Comparative analysis of activation times of circadian-related genes across tissues. BMC Bioinformatics, 2006, 7, 87. [Abstract] (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=16504088&query_hl=4&itool=pubmed_docsum)
8. Huang, W., Umbach, D.M., and Li, L. Accurate anchoring alignment of divergent sequences. Bioinformatics, 2006, 22, 29. [Abstract] (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=16301203&query_hl=1&itool=pubmed_docsum)
9. W. Huang, U. Ohler, D.M. Umbach, and L. Li Optimized mixed Markov models for motif identification. BMC Bioinformatics, 2006, 7, 279 [Abstract] (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=16749929&query_hl=11&itool=pubmed_docsum)
10. L. Li, Y. Liang, and R. L. Bass. GAPWM: A genetic algorithm method for optimizing a position weight matrix. Bioinformatics, 2007, doi:10.1093/bioinformatics/btm080 [Download the PDF] (http://bioinformatics.oxfordjournals.org/cgi/reprint/btm080?ijkey=Yt96fDce5rklKGu&keytype=ref)
11. Li, L., Bass, R.L., Liang, Y. fdrMotif: Identifying cis-elements by an EM Algorithm Coupled with False Discovery Rate Control. Bioinformatics 2008; 25, 629-636, doi: 10.1093/bioinformatics/btn009 [Download the PDF] (http://bioinformatics.oxfordjournals.org/cgi/reprint/btn009?ijkey=v4eNL6p1vQT3zxr&keytype=ref)
12. Li L, Bass RL, Liang Y. fdrMotif: Identifying cis-elements by an EM algorithm coupled with false discovery rate control. Bioinformatics (Oxford, England) 2008 24(5):629-636. [Abstract] (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=18296465)

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