Li Xue
Iowa State University 1-515-450-7183(C) lixue@iastate.edu http://www.cs.iastate.edu/~lixue/
PROFILE
Ph.D. student with major in Bioinformatics and minor in Statistics. Major research areas are data
mining/machine learning applications in QSAR (Quantitative Structure–Activity Relationship)
models, macro-molecular binding sites predictions, T cell epitope predictions, and ranking
docked models using partner-specific interface predictions.
SKILLS
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Machine learning algorithms
Proficient in Perl, MATLAB, R
Familiar with Linux
Experience with SAS
EDUCATION
Iowa State University
Ph. D.
2012
Bioinformatics with Statistics minor
GPA: 3.75/4
Major Prof. Vasant Honavar and Drena Dobbs
Dissertation: Sequence homology based protein-protein interacting residue predictions and the
applications in ranking docked conformations.
Shanghai Jiaotong University
M. S.
2003
Image Processing and Pattern Recognition
GPA: 3.93/4
Major Prof. Lixiu Yao and Jie Yang
Thesis: Data mining-based gene expression data analysis and prediction of signal peptides and its
cleavage site.
Yanshan University
B. E.
Electrical and Electronics Engineering
1999
GPA: 3.55/4(top 5%)
Major Prof. Xiuling Zhang
Thesis: The optimization of dynamic RBF neural network and its application.
HONORS & AWARDS
Best Poster Award at ACM-BCB
2011
Women in Bioinformatics Award at ACM-BCB
2011
Li Xue
Iowa State University 1-515-450-7183(C) lixue@iastate.edu http://www.cs.iastate.edu/~lixue/
ISMB Travel Fellowship
Exceptional Graduate
2010
2003, 2006
Scholastic Excellent Graduation Thesis for Bachelor Degree
2003
Special Prize of Academic Excellence Scholarship (top 1%)
2002
The First and Second Prize of Academic Excellence Scholarship
1999-2001
Exceptional Student
1999-2000
JOURNAL PAPERS
Xue, L. C., Jordan, R., El-Manzalawy, Y., Dobbs, D., & Honavar, V. (2012). DockRank: Ranking
docked models using partner-specific sequence homology based protein interface prediction. (To
be submitted.)
Walia, R., Xue, L. C., Wilkins, K., El-Manzalawy, Y., Dobbs, D., and Honavar, V. (2012) Robust
prediction of RNA-binding sites in proteins using a combination of sequence homology and
machine learning methods. (To be submitted.)
Xue, L. C., Dobbs, D., & Honavar, V. (2011). HomPPI: A Class of sequence homology based proteinprotein interface prediction methods. BMC Bioinformatics, 12, 244.
Zhang, G. L., Ansari, H. R., Bradley, P., Cawley, G. C., Hertz, T., Hu, X., Jojic, N., Kim, Y., Kohlbacher,
O., Lund, O., Lundegaard, C., Magaret, C. A., Nielsen, M., Papadopoulos, H., Raghava, G. P.,
Tal, V. S., Xue, L. C., Yanover, C., Zhu, S., Rock, M. T., Crowe, J. E., Panayiotou, C.,
Polycarpou, M. M., Duch, W., & Brusic, V. (2011). Machine learning competition in
immunology - Prediction of HLA class I binding peptides. J Immunol Methods, 374 (1-2), 1-4.
Xue, L. C., Petersen, L. K., Broderick, S., Narasimhan, B., & Rajan, K. (2010). Identifying factors
controlling protein release from combinatorial biomaterial libraries via hybrid data mining
methods. ACS Combinatorial Science, 13, 50-58.
Petersen, L. K., Xue, L. C., Wannemuehler, M.J., Rajan, K., & Narasimhan, B. (2009). The simultaneous
effect of polymer chemistry and device geometry on the in vitro activation of murine dendritic
cells. Biomaterials, 30, 5131-5142.
Lee, J. H., Hamilton, M., Gleeson, C., Caragea, C., Zaback, P., Sander, J. D., Xue, L. C., Wu, F.,
Terribilini, M., Honavar, V., & Dobbs, D. (2008). Striking similarities in diverse telomerase
proteins revealed by combining structure prediction and machine learning approaches. Pac Symp
Biocomput, 501-12.
Li Xue
Iowa State University 1-515-450-7183(C) lixue@iastate.edu http://www.cs.iastate.edu/~lixue/
Xue, L. C., Yang, J., & Liu, H. (2006). Multi-feature Image Segmentation using FCM algorithm. Image
Technology, 1, 34-35.
Li, G. Z., Yang, J., Liu, G.P., & Xue, L. C. (2004). Feature selection for multi-class problems using
support vector machines. Lecture Notes In Artificial Intelligence, 3157, 292-300.
Liu, H., Yang, J., Wang, M., Xue, L. C., & Chou, K. C. (2005). Using Fourier Spectrum Analysis and
Pseudo Amino Acid Composition for Prediction of Membrane Protein Types. The Protein
Journal, 24(6), 385-389.
CONFERENCE PAPERS
Xue, L. C., Jordan, R., El-Manzalawy, Y., Dobbs, D., & Honavar, V. (2011). Ranking docked models of
protein-protein complexes using predicted partner-specific protein-protein interfaces: A
preliminary study. In Proceedings of the International Conference On Bioinformatics and
Computational Biology (ACM-BCB); Chicago, Illinois, August 1-3, 2011. (Best Poster Award
and an extended version was invited to a special issue of BMC Bioinformatics journal.)
Xue, L. C., Walia, R., EL-Manzalawy, Y., Dobbs, D., & Honavar, V. (2011). Improved prediction of
protein-RNA interfaces using combined sequence homology and machine learning methods: A
preliminary study. In Proceedings of the International Conference On Bioinformatics and
Computational Biology (ACM-BCB); Chicago, Illinois, August 1-3, 2011.
Yao, L., Xue, L. C., Liu, H. (2007). A novel approach predicting the signal peptides and their cleavage
sites, International Conference on Bioinformatics & Biomedical Engineering, 8, 391-393.
PROFESSIONAL EXPERIENCE
 DockRank: Rank Docked Conformations
Fall 2010 - Fall 2011
Used our protein sequence-based partner-specific interface prediction to predict interface residues
between a receptor and a ligand. Ranked the docked models generated by Cluspro, Gramm-X, ZDock
based on the agreement of predicted interface residues and the docked interface residues. Our scoring
function was compared with several energy-based scoring functions and several start-of-the-art interface
predictors, and showed significant improvement.
 PS-HomPPI: Partner-Specific Protein-Protein Interface Prediction
Spring 2010- Fall 2010
Investigated the interface conservation of transient interactions. Designed a sequence homology partnerspecific interface predictor. Showed that the knowledge of a specific interacting partner can help to
improve the prediction performance.
Li Xue
Iowa State University 1-515-450-7183(C) lixue@iastate.edu http://www.cs.iastate.edu/~lixue/
 Intern at Rahway, Merck & Co., Inc.
Summer 2009
Compared several published algorithms MHC Class II epitope prediction. Designed, developed, and
tested a new epitope prediction algorithm, which is a modification of Hammer's matrix method that
showed an improved performance compared to other methods.
 QSAR: In Silico Analysis of Biodegradable Drug Delivery System
2008
Developed a GA-SVR hybrid system for selecting relevant copolymer molecular descriptors polymer
film stimulation data. Genetic Algorithms (GA) was used to selected the optimal subset of copolymer
molecular descriptors that optimize the regression performance of SVR on polymer film stimulation data.
 GA-LLE based Regression Analysis of Spinel Data
Fall 2008
Applied Genetic Algorithms (GA) to find the optimal parameters for LLE (Locally Linear Embedding),
which was used to reduce the dimension of feature space for SVR (Support Vector Regression).
Significantly improved the regression performance of SVR from 0.7386 (original 52-dimension space) to
0.9105 (14-dimension LLE space).
 Netflix Competition – Movie Recommendation Systems
2008
Led a group of three graduate students. Instead of using user’s profile, we downloaded, extracted and
utilized many properties of the movies, such as actors, director, genres and awards information. Designed
and developed a set of similarity based approach, PCA based SVM classification, and regression
solutions to predict a user’s ranking of movies.
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NPS-HomPPI: Non-Partner Specific Homologous Sequence-Based Protein-Protein Interface
Prediction
Spring 2007- Summer 2010
Applied PCA to study the multivariate relationship between protein interface conservation and multiple
sequence similarity metrics; Developed NPS-HomPPI interface predictor, with performance rivaling more
complicated methods that require structural information as input.
 Classification of Signal Peptide and Prediction of Cleavage Site
Designed the classifiers using SVM/HMM; Dealt with unbalanced dataset;
2005
 Multi-Feature Image Segmentation using FCM Algorithm
Summer 2005
Used fuzzy c-means clustering algorithm to segment a picture into several meaningful areas.
Li Xue
Iowa State University 1-515-450-7183(C) lixue@iastate.edu http://www.cs.iastate.edu/~lixue/
 Image Processing: Character Recognition (course project)
Spring 2005
Trained BP and Hopfield Neural Network (NN) using labeled character sample set, and used the trained
NN classifier to identify noisy characters.
 Speech Enhancement (course project)
Fall 2004
Studied and implemented four basic adaptive speech enhancement algorithms based on LMS and Wavelet
Decomposition.
 Clustering Analysis of Gene Expression Profile
Spectral estimation of optimal cluster numbers; Dealt with incomplete datasets;
Fall 2004-Spring 2005
 Optimal Design and Application of RBF Neural Network (Bachelor thesis Project)
Spring 2003
Designed fuzzy Neural Network temperature controller (FNNC); Used GA to optimize the parameters of
FNNC; Used an RBF NN to simulate the temperature system to be controlled.