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Yijun
Sun, Ph.D.
Interdisciplinary
Department of Electrical and
Computer Engineering University
of Florida
Email: sunyijun {at} biotech.ufl.edu |
I received M.
Sc and Ph.D. degrees in electrical engineering from the University
of Florida,
Patience
and diligence, like faith, remove mountains. - William Penn (1644-1718)
Stay
hungry, stay foolish. - Steve Jobs (1955-2011)
Two Postdoctoral Associate Position Available
(Positions have been filled)
One
Graduate Assistant Position Available
My Research Interests
o
Bioinformatics:
metagenomics,
sequence analysis, microarray data analysis, microbial community analysis,
molecular classification and genetic network modeling for cancer diagnosis and
prognosis, microbial network analysis, phylogenetic analysis
o Machine Learning/Data Mining: large margin classification/regression, large-scale clustering analysis, ensemble learning, feature selection/extraction, computational learning theory, network analysis, graphical modeling and Bayesian network.
My Projects
o The D Project funded by NSF
o The L Project funded by Florida Biomedical Research Program
o The E Project
My Postdocs and Students
o
Dr.
Yunpeng Cai
(Postdoc, 2007-2011. Now Associate Professor with the Chinese Academy of
Sciences)
o
Dr.
Xiaoyu Wang (Postdoc, 2010-)
o
Dr.
Ying Tang (Postdoc, 2011-)
o
Dr.
Karthik Gurumoorthy
(Postdoc, 2011-)
o
Dr.
Yun Li (Visiting scholar, 2012-2013, Associate Professor with the Nanjing
University of Posts & Telecommunications, China)
o
Jin
Yao (PhD student, 2011-)
o
Hedjazi
Lyamine (PhD student at University of Toulouse - France, External committee
member)
o
Qian Chen (Ph.D.
Student, Committee member)
o
Lei
Yang (Ph.D. Student, Committee member)
o
Bing
Han (Ph.D. Student, Committee member)
o
Jun
Xu (Ph.D. Student, Committee member)
o
Taoran
Lu (Ph.D. Student, Committee member)
o
Ming
Xue (Ph.D. Student, Committee member)
o
Lin
Du (Ph.D. Student, Committee member)
o
Jun
Ling (Ph.D. Student, Committee member)
o
Yubo
Cheng (Master Student, graduated in 2009)
My Publications
o
Y. Sun and Y. Cai,
Inferring Microbe-microbe
Interactions Using Large Collections of 16S rRNA Pyrosequences,
Technical
Report, 2011.
o
Y.
Cai* and Y. Sun*,
ESPRIT-Forest:
Taxonomy Independent Analysis of Tens of Millions of 16S rRNA
Pyrosequences Using Parallel Computing,
Technical Report,
2011.
o
C. Rosser, V. Urquidi,
Y. Cai, Y. Sun, and S. Goodison,
Molecular
Biomarker Signature for the Non-Invasive Detection of Bladder Cancer,
Journal of Clinical Oncology, submitted,
2011.
o
D.
Boucias, Y. Cai, Y. Sun, V. U. Lietze,
R. Sen, R. Raychoudhury,
and M. Scharf,
The
Microbiome of the Lignocellulosedegrading
Termite Reticulitermes Flavipes:
Resistance to Perturbation in Response to Diet,
FEMS
Microbiology Ecology,
submitted, 2011.
o
M.
Ukhanova, T. Culpepper, D. Baer, D. Gordon, S. Kanahori, J. Valentine, J. Neu, Y. Sun, X. Wang, V. Mai,
Gut Microbiota Correlates with Energy Gain from a Dietary Fiber
and Appears Associated with Acute and Chronic Intestinal Diseases,
Clinical
Microbiology and Infection, accepted, 2011. (impact factor: 4.8)
o
X.
Wang, Y. Cai, Y. Sun, R. Knight, V. Mai,
Secondary
Structure Information Does not Improve OTU Picking for 16S rRNA
Sequences,
The
ISME Journal,
in press. (impact factor: 6.2)
o
A-L.
Paul, A. Zupanska, D. Ostrow,
Y. Zhang, Y. Sun, J. Li, S. Shanker, W. Farmerie, C. Amalfitano, R. J. Ferl,
Spaceflight Transcriptomes: Unique Responses to a Novel Environment,
Astrobiology, in press. (impact factor: 2.4)
o
V.
Mai, C. M. Young, M. Ukhanova, X. Wang, Y. Sun, G. Casella, D. Theriaque, N. Li, R. Sharma, M. Hudak,
J. Neu,
Fecal
Microbiota in Premature Infants Prior to Necrotizing Enterocolitis,
PLoS ONE, 6(6): e20647, 2011. (impact factor: 4.4)
o
Y.
Cai* and Y. Sun*, [Website]
Nucleic Acids
Research,
39 (14): e95, 2011. (impact factor: 7.8)
o
Y. Sun*, Y. Cai*, S. Huse, R. Knight, W. Farmerie, X. Wang and V. Mai,
(*equal contribution)
Briefings in Bioinformatics, in press,
2011. (impact factor: 9.3)
o
Y. Sun and Y. Cai,
Estimating Species Richness Using Large Collections of 16S rRNA Pyrosequences,
Handbook
of Molecular Microbial Ecology: Metagenomics
and Complementary Approaches (Edited
by Frans J. de Bruijn),
Wiley-Blackwell,
2011.
o
Y.
Cai, H. Lyamine, Y. Sun, and S. Goodison,
Fast Implementation of ℓ1 Regularized Learning Algorithms Using Gradient Descent Methods,
IEEE Trans. on
Pattern Analysis and Machine Intelligence, submitted,
2010.
o
Y. Sun*, Y. Cai*, V.
Mai, W. Farmerie, F. Yu, J. Li, and S. Goodison, (*equal contribution)
Nucleic Acids
Research,
vol. 38, no. 22, e205, 2010 (impact
factor: 7.8)
o
Y. Sun*, Y. Cai*, L.
Liu, F. Yu, M. L. Farrell, W. McKendree, and W. Farmerie, (*equal contribution)
ESPRIT: Estimating Species Richness Using Large Collections of 16S rRNA Pyrosequences,
Nucleic
Acids Research,
vol. 37, no. 10 e76, 2009. (impact factor: 7.8)
The algorithm has been used by
more than 180 major research institutes worldwide.
o Y. Sun,
Local Learning Based Feature
Selection for High Dimensional Data Analysis,
IEEE Trans. on Pattern Analysis and
Machine Intelligence (TPAMI), vol. 32, no. 9, pp. 1610-1626, 2010. (impact factor: 6.0, the overall
top-ranked IEEE transactions journal)
This paper is
featured as Spotlight Paper in the
September 2010 issue of TPAMI.
o
S.
Goodison, Y. Sun, and V. Urquidi,
Review: Derivation
of Cancer Diagnostic and Prognostic Signatures from Gene Expression Data,
Bioanalysis, vol. 2, no. 5, pp. 855-862, 2010.
o Y. Sun, V. Urquidi, and S. Goodison,
Breast Cancer Research and Treatment, vol. 119, no. 3, pp. 593-599, 2010. (impact factor: 5.7)
o C. Pascoe, A. Lawande, H. Lam, A. George, Y. Sun, W. Farmerie, and H. Martin
in Proc 2010 Symposium on Application Accelerators in High-Performance Computing (SAAHPC10), July 2010. (oral presentation)
o
V.
Mai, and Y. Sun,
New 16S rRNA Sequence Data Mining
Tools Help Identify Gut Microbes Associated with Colorectal Polyp Prevalence,
The
Rowett-INRA 2010 Conference on Gut Microbiology: New Insights into Gut
Microbial Ecosystems,
June 2010.
o Y. Cai, Y. Sun, Y. Cheng, J. Li, and S. Goodison,
Fast Implementation of ℓ1 Regularized Learning Algorithms Using Gradient Descent Methods,
in Proc 10th
SIAM International Conference on Data Mining (SDM), pp. 862-871,
April 2010.
(oral presentation/acceptance rate: 82/351 = 23%)
o
F.
Yu*, Y. Sun*, L. Liu, and W. Farmerie, (*equal contribution)
GSTaxClassifier: A Genomic Signature Based Taxonomic Classifier for Metagenomics Data Analysis,
Bioinformation, vol. 4, no.
1, pp. 46-49, 2009.
o
N.
Bandyopadhyay, T. Kahveci, S. Ranka, Y. Sun and S. Goodison,
Pathway based Feature
Selection Algorithm for Cancer Microarray Data,
Advances
in Bioinformatics,
532989, 2009.
o
L.
Yin, L. Liu, Y. Sun, R. R. Gray, A. C. Lowe, W. Hou, J. W.
Sleasman, and M. M. Goodenow,
Ultra-deep
Pyrosequencing Captured Low Frequency CXCR4 Virus Populations Co-archived with
CCR5 Virus in Peripheral Blood Lymphocytes from HIV-infected Therapy-naive
Children,
The
17th Conference on Retroviruses and Opportunistic Infections (CROI 2010), San Francisco,
CA, February 2010.
o
Y.
Duan, L. Zhou, D. Hall, W. Li, H. Doddapaneni, H. Lin, L. Liu, C. Vahling, D.
Gabriel, K. Williams, A. Dickerman, Y. Sun, and T. Gottwald,
Molecular
Plant-Microbe Interactions, vol. 22, no. 8, 2009, pp. 1011-1020, 2009. (impact factor: 4.3)
o Y. Sun* and S. Goodison* (equal contribution)
Optimizing Molecular
Signatures for Predicting Prostate Cancer Recurrence,
The
Prostate,
vol. 69, no. 10, pp. 1119-27, 2009. (impact factor: 3.7)
This paper was featured in Medical News Today.
o Y. Cai, Y. Sun, J. Li, and S. Goodison,
Online
Feature Selection Algorithm with Bayesian L-1 Regularization,
in Proc. 13th Pacific-Asia Conference on Knowledge
Discovery and Data Mining (PAKDD09), Bangkok, Thailand, April 2009. (oral
presentation: 39/338 = 12%)
o
M.
L. Farrell, W. Norrie, V. Ryan, K. Brown, R. Winegar, Y. Sun, L. Liu, W. Farmerie, and W. McKendree,
Metagenomic Analysis of Air,
The 2009 Gordon Research Conferences
on Chemical and Biological Terrorism Defense, Galveston, TX, January 2009.
o
C.
Rosser, L. Liu, Y. Sun, P.
Villicana, M. McCullers, S. Porvasnik, and S. Goodison
Bladder Cancer
Associated Gene Expression Signatures Identified by Profiling of Exfoliated
Urothelia,
Cancer
Epidemiology, Biomarkers and Prevention, vol. 18, no. 2, pp. 444-453, 2009.
(impact factor: 4.8)
o
Y. Sun, and D. Wu
Feature Extraction
through Local Learning,
Statistical Analysis and Data Mining, vol. 2, no.
1, pp. 34-47, 2009.
o
Y.
Cheng, Y. Cai, Y. Sun, and J. Li
Semi-supervised
Feature Selection under the Logistic I-RELIEF Framework,
in Proc. 19th International Conference on
Pattern Recognition (ICPR08), Tampa, FL, December 2008.
(oral
presentation: 18%)
o
Y. Sun, Y.
Cai, and S. Goodison
Combining Nomogram and Microarray Data for Predicting Prostate Cancer
Recurrence,
in Proc.
8th IEEE International Conference on Bioinformatics and Bioengineering
(BIBE08), pp. 1-7, Athens, Greece, October 2008.
o
Y. Sun and D. Wu
A RELIEF Based Feature Extraction
Algorithm [Matlab code]
in Proc. 8th
(oral
presentation: 40/282 = 13%)
o
Y. Sun, S.
Todorovic, and S. Goodison
A
Feature Selection Algorithm Capable of Handling Extremely Large Data
Dimensionality [Matlab code]
in Proc. 8th SIAM International Conference on
Data Mining (SDM08), pp. 530-540, April 2008.
(acceptance rate: 72/282 = 25%)
o
Y. Sun
Iterative RELIEF for Feature Weighting: Algorithms, Theories, and Applications [Website]
IEEE Trans. on Pattern Analysis and
Machine Intelligence (TPAMI), vol. 29, no. 6, pp. 1035-1051, June
2007. (impact factor: 6.0)
o
Y. Sun, S. Goodison,
J. Li, L. Liu, and W. Farmerie
Improved Breast Cancer
Prognosis through the Combination of Clinical and Genetic Markers
Bioinformatics, vol. 23, no. 1, pp. 30-37, January 2007. (impact factor: 5.0)
This
paper was among the 50 most-frequently read articles in Bioinformatics. Dec.
2006 (29th), Jan. 2007 (5th), Feb. 2007 (44th). It is featured in MATLAB
Digest--Biotech and Pharmaceutical Edition (vol. 1, no. 2, June
2007).
o
Y. Sun, S. Todorovic,
and J. Li
Unifying
Multi-Class AdaBoost Algorithms with Binary Base
Learners under the Margin Framework
Pattern
Recognition Letters (PRL), vol. 28, no. 5, pp. 631-643, April 2007.
o
Y. Sun
Feature
Weighting through Local Learning
Computational
Methods of Feature Selection, H. Liu and H. Motoda (eds.), Chapman
and Hall/CRC Press, October 2007.
o
Y. Sun and J. Li
Iterative RELIEF for
Feature Weighting
in
Proc. International Conference on
Machine Learning (ICML06), vol. 29, pp. 1035-1051, June 2006.
(acceptance
rate 140/700 = 20%)
o
Y. Sun, S. Todorovic, J. Li, and D. O. Wu
Unifying Error-Correcting
and Output-Code AdaBoost within the Margin Framework,
in
Proc. International Conference on
Machine Learning (ICML05), vol. 119, pp. 872-879, August 2005.
(acceptance
rate 134/491 = 27%) [Matlab code]
o
Y. Sun, Z. Liu, S.
Todorovic and J. Li
Adaptive Boosting for Synthetic
Aperture Radar Automatic Target Recognition,
IEEE Trans. on
Aerospace and Electronic Systems (TAES), vol. 43, no. 1, pp. 112-125, January
2007.
o
Y. Sun and
Predicting
Breast Cancer Metastasis by Integrating Both Clinical and Genetic Markers,
in Proc. International Conference on
Bioinformatics and Computational Biology (BIOCOMP07), vol. 1, pp. 229-235,
June 2007.
(acceptance
rate = 27%)
o
Y. Sun, F. Yu, L.
Liu, and W. Farmerie
Estimating Microbial
Population Densities Based on Genomic Signatures,
in
Proc. International Conference on
Bioinformatics and Computational Biology (BIOCOMP07), vol. 1, pp. 163-168,
June 2007.
(acceptance
rate = 27%)
o
Y. Sun, L. Liu, M. Popp, and
Estimation of Cross-hybridization
Signals Using Support Vector Regression,
in
Proc. IEEE Symposium of Computations in Bioinformatics and Bioscience
(SCBB06), vol. 1, pp. 17- 21, June 2006.
o
Y. Sun, S.
Todorovic, and J. Li
Reducing the Overfitting of AdaBoost by Controlling its Data Distribution Skewness,
International Journal of Pattern Recognition and
Artificial Intelligence (IJPRA), vol. 20, no. 7, pp. 1093-1116,
November 2006.
o
Y. Sun, S. Todorovic, and J. Li,
Increasing
the Robustness of Boosting Algorithms within the Linear-Programming Framework,
Journal
of VLSI Signal Processing Systems, vol. 48, no. 1-2, pp. 5-20, August
2007.
o
Y. Sun and J. Li
Adaptive Learning Approach to Landmine Detection,
IEEE Trans. on Aerospace
and Electronic Systems (TAES), vol. 41,
no. 3, pp. 973-985, July 2005.
o
Y. Wang, X. Li, Y. Sun, J. Li and P. Stoica
Adaptive Imaging for Forward-looking Ground Penetrating Radar,
IEEE Trans. on Aerospace and Electronic Systems (TAES), vol. 41, no. 3, pp. 922-936, July 2005.
o Y. Sun, X. Li and J. Li
Practical Landmine Detector Using Forward-Looking Ground Penetrating
Radar,
IEE Electronics Letters, vol. 41,
pp.97-98, January 2005.
o
Y. Sun, S.
Todorovic, J. Li, and D. O. Wu
A Robust Linear-programming Based Boosting Algorithm,
in Proc. IEEE International
Workshop on Machine Learning for Signal Processing (MLSP05), Mystic, CT, September 2005.
o
Y. Sun, J. Li, and
W. Hager
Two New Regularized AdaBoost Algorithms,
in Proc.
International Conference on Machine Learning and Applications (ICMLA04),
pp. 41- 48, Louisville, KY, December 2004.
o
Y. Sun and J. Li,
IEE Proc.-Radar, Sonar and Navigation, special issue on Time-Frequency
Analysis and Feature Extraction, vol. 150,
pp. 253-261, August 2003.
o Y. Sun, M. Xue, J. Li, and S. R. Stanfill,
Improving ATR Performance through Distance Metric Learning,
in Proc. of SPIE on Technologies and Systems
for Defense and Security (SPIE07),
o Y. Sun and J. Li,
Landmine Detection Using Forward-looking Ground Penetrating Radar,
in Proc. of SPIE on Technologies and Systems
for Defense and Security (SPIE05), vol. 5794, pp. 1089-1097, Orlando, FL,
April 2005.
o Q. Liu, Y. Sun, and J. Li,
Automatic Target Recognition with Bayesian Networks for Wide-area
Airborne Minefield Detection,
in Proc. of SPIE on Technologies and Systems
for Defense and Security (SPIE05), vol. 5794, pp. 1060-1070, Orlando, FL,
April 2005.
o
Y. Sun, Z. Liu, S.
Todorovic, and J. Li,
SAR Automatic Target Recognition Using AdaBoost,
in Proc. of
SPIE on Technologies and Systems for Defense and Security (SPIE05), vol. 5808,
pp. 282-293, Orlando, FL, April 2005.
o Y. Sun and J. Li,
Boosting a
Wavelet Packet Transform Based Landmine Detector,
in Proc. of SPIE on Technologies
and Systems for Defense and Security (SPIE04), vol. 5415, pp. 1300-1309,
o Y. Sun and J. Li,
Detect Buried Plastic Mines Using Time-frequency
Analysis,
in Proc. of SPIE on Detection and Remediation Technologies for Mine
and Minelike Targets (SPIE03), vol. 5089, pp. 851-862,
US Patents
o Y. Sun, and J. Li,
Land Mine Detector, Patent No.
o V. Mai, J. Byatt, and Y.
Sun, Microbiota Profiling to Identifying Subjects
at Increased Risk for CRC, pending, 2011.
o Y. Sun, S. Goodison, and L Liu, Methods of Feature Selection through
Local Learning; Breast and Prostate Cancer Prognostic Markers, WO/2009/067655, International Application No.: PCT/US2008/084325, 2009.
Reviewers for:
Nucleic Acids Research,
Bioinformatics, Genome Research, Genome Biology, IEEE Trans. on Pattern
Analysis and Machine Intelligence, IEEE Trans. on Knowledge and Data
Engineering, Applied and Environmental Microbiology, Frontiers in Bioscience,
The ISME Journal, IEEE Trans. on Neural Networks, Applied and Environmental Microbiology,
IEEE Trans. on Fuzzy Systems, Journal of Pattern Recognition Research,
Neurocomputing, Pattern Recognition, Pattern Recognition Letters, Computational
Optimization and Applications, IEE Proceedings -Radar, Sonar and Navigation,
IEEE Signal Processing Letters, IEEE Trans. on Aerospace and Electronic
Systems, IEEE Trans. on Instrumentation and Measurement, IEEE Trans. Geoscience
and Remote Sensing, Biomedical Signal Processing and Control, Chinese Optics
Letters, Knowledge and Information Systems, Artificial Intelligence
Review
Editorial Board:
Frontiers in
Evolutionary and Genomic Microbiology (2011-)
Frontiers in Genetics (2011-)
Some Links:
o IEEE
Trans. on Pattern Analysis and Machine Intelligence
o Journal
of Machine Learning Research
o
International Conference on Machine Learning
o
SIAM International
Conference on Data Mining
Some Pictures of Beautiful
China:
o Taken by
Dr. Dimitri Bertsekas
o If we knew what it was we were doing, it would not be called research,
would it? - Albert Einstein (1879-1955)
o A stroke of
genius: striving for greatness in all you do. - Richard Hamming (1915-1998)