Li (Lily) Chen

 Ph.D.

  Computational Bioinformatics and Bio-imaging Laboratory (CBIL)
  Electrical and Computer Engineering, Virginia Tech

  Address:    4300 Wilson Blvd., Suite 750
                     Arlington, VA 22203
  Phone:       (703)387-6049
  Email:        lchen06@vt.edu

I was a Ph.D. student and Research Assistant at the Computational Bioinformatics and Bioimaging Laboratory in the Department of ECE at Virginia Tech. My research focuses on machine learning, data mining and pattern recognition in bioinformatics and computational biology. I am interested in integrative modeling and analysis of multiple high-throughput biological data for cancer research. 

  Education

Jan. 2007 - Dec. 2010

Ph.D. Student, Electrical and Computer Engineering, Virginia Tech

Sept. 2004 - May 2006

M.S., Computer Science and Engineering, University of South Florida

Sept. 2001 - Mar. 2004

M.S., Computer Science and Engineering, Shanghai Jiaotong University

Sept. 1996 - June 2000

B.S., Computer Science and Engineering, Beijing Information and Technology Institute

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  Research Interests

Computational Biology

- Knowledge-guided biomarker identification

- Multi-level data integration for condition specific regulatory network reconstruction

- MRF-based subnetwork identification and network-constrained SVMs for cancer prediction

Pattern Recognition and Machine Learning

- Feature selection, classification and prediction

- Data mining and integration

- Network learning and inference

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  Publications

Peer-reviewed Journal Publications

L. Chen, J. Xuan, R. B. Riggins, Y. Wang, E. Hoffman, and R. Clarke, "Multi-level Support Vector Regression Analysis to Identify Condition-specific Regulatory Networks," Bioinformatics, 2010. (doi: 10.1093/bioinformatics/btq144; in press).

L. Chen, J. Xuan, C. Wang, S. I.-M., Y. Wang, Z. Zhang, and R. Clarke, "Biomarker identification by knowledge-driven multi-level ICA and motif analysis," Intl J. Data Mining and Bioinformatics, vol. 3, pp. 365-381, 2009.

L. Chen, J. Xuan, R. B. Riggins, Y. Wang, E. Hoffman, and R. Clarke, "Identification of Condition-specific Regulatory Modules by Multi-level Motif and mRNA Expression Analysis," Intl J. of Computational Biology and Drug Design, vol. 2, pp. 1-20, 2009.

L. Chen, J. Xuan, C. Wang, M. Shih Ie, Y. Wang, Z. Zhang, E. Hoffman, and R. Clarke, "Knowledge-guided multi-scale independent component analysis for biomarker identification," BMC Bioinformatics, vol. 9, p. 416, 2008.

R. B. Riggins, J. P. Lan, Y. Zhu, U. Klimach, A. Zwart, L. R. Cavalli, B. R. Haddad, L. Chen, T. Gong, J. Xuan, S. P. Ethier, and R. Clarke, "ERRgamma mediates tamoxifen resistance in novel models of invasive lobular breast cancer," Cancer Res, vol. 68, pp. 8908-17, Nov 1 2008.

C. Wang, J. Xuan, L. Chen, P. Zhao, Y. Wang, R. Clarke, and E. Hoffman, "Motif-directed network component analysis for regulatory network inference," BMC Bioinformatics, vol. 9 Suppl 1, p. S21, 2008.

Conference Publications

L. Chen, J. Xuan, Y. Wang, R. B. Riggins, and R. Clarke, "Network-constrained SVM for Classification," in Proceedings of the 2008 Seventh International Conference on Machine Learning and Applications San Diego, CA: IEEE Computer Society, 2008, pp. 60-65.

L. Chen, J. Xuan, R. B. Riggins, Y. Wang, E. P. Hoffman, and R. Clarke, "Identification of Condition-specific Regulatory Modules by Multi-level Motif and mRNA Expression Analysis," in The 2008 Intl Conference on Bioinformatics & Computational Biology Las Vegas, Nevada, 2008.

T. Gong, J. Xuan, L. Chen, R. B. Riggins, Y. Wang, E. Hoffman, and R. Clarke, "Sparse Decomposition of Gene Expression Data to Infer Transcriptional Modules Guided by Motif Information," in Proc. Fourth Intl Symposium on Bioinformatics Research and Applications Atlanta, GA, 2008.

C. Wang, J. Xuan, L. Chen, R. B. Riggins, E. Hoffman, and R. Clarke, "Reliability Analysis of Transcriptional Regulatory Networks," in Proc. Intl Conf. on Bioinformatics, Computational Biology, Genomics and Chemoinformatics Orlando, FL, 2008.

C. Wang, J. Xuan, L. Chen, P. Zhao, Y. Wang, R. Clarke, and E. Hoffman, "Integrative Network Component Analysis for Regulatory Network Reconstruction," in Proc. Fourth Intl Symposium on Bioinformatics Research and Applications Atlanta, GA, 2008.

L. Chen, C. Wang, S. I.-M., T.-L., Wang, Z. Zhang, Y. Wang, R. Clarke, E. Hoffman, and J. Xuan, "Biomarker Identification by Knowledge-Driven Multi-Level ICA and Motif Analysis," in Proc. Intl Workshop on Machine Learning Methods in Biomedicine and Bioinformatics Cincinnati, OH, 2007.

L. Chen, J. Xuan, R. Clarke, and Y. Wang, "Biomarker Identification by Knowledge-Driven Multi-Scale Independent Component Analysis," in Proc. Third IEEE-NIH Life Science Systems and Applications Workshop Bethesda, MD, 2007. (Best student's paper).

Other Publications

S. Fefilatyev, L. Chen, T. V. Ivanovskiy, L. O. Hall, D. B. Goldgof, H. Greenstein, and C. R. Garrett, "Complications in using automated methods to increase clinical trial accrual," Intl. J Biomedical Engineering and Technology, To appear.

L. Chen, D. B. Goldgof, L. O. Hall, and S. Eschrich, "Noise-based Feature Perturbation as a Selection Method for Microarray Data," in Proc. Third Intl Symposium on Bioinformatics Research and Applications Atlanta, GA, 2007.

L. Chen, L. Li, D. Goldgof, F. George, Z. Chen, A. Rao, J. Cragun, R. Sutphen, and J. Lancaster, "Improving Reliability of Response Prediction to Platinum-Based Therapy by AdaBoost and Multiple Classifiers," Conf Proc IEEE Eng Med Biol Soc, vol. 5, pp. 4822-5, 2005.

L. Li, L. Chen, D. Goldgof, F. George, Z. Chen, A. Rao, J. Cragun, R. Sutphen, and J. Lancaster, "Integration of clinical information and gene expression profiles for prediction of chemo-response for ovarian cancer," in Conf Proc IEEE Eng Med Biol Soc, 2007/02/07 ed. vol. 5, 2005, pp. 4818-21.

L. Li, Z. Wu, L. Chen, F. George, Z. Chen, A. Salem, M. Kallergi, and C. Berman, "Breast Tissue Density and CAD Cancer Detection in Digital Mammography," in Conf Proc IEEE Eng Med Biol Soc, 2007/02/07 ed. vol. 3, 2005, pp. 3253-6.

L. Chen, F. Qi, "An Improved Learning Algorithm of Synergetic Neural Networks Based on Gradient Dynamics, " Journal of Image and Graphics, " vol.8 (A). Spec, 466-470, 2003. (in Chinese).

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Last Updated: Dec. 02, 2009