Ting Chen
Department of Biological Sciences
University of
Southern California
Los Angeles, CA 90089-2910 USA
Next Generation Sequencing
5.
Wan L, Yan X, Chen
T and Sun F (2012) Modeling
RNA degradation for RNA-Seq with applications.
Biostatistics,
2012; doi: 10.1093/biostatistics/kxs001.
6. Mehta G, Deelman E, Knowles J, Chen T, et al. (2012) Enabling
Data and Compute Intensive Workflows in Bioinformatics. Lecture Notes in Computer Science, 2012, Volume 7156, EURO-PAR 2011: PARALLEL PROCESSING
WORKSHOPS, Pages 23-32. DOI:10.1007/978-3-642-29740-3_4.
7.
Chang Q, Luan Y, Chen T, Fuhrman J and Sun F
(2011) Computational methods for the analysis of tag sequences in metagenomics studies. Frontiers in Bioscience, S4, 1333-1343, June
1.
8. Wang Y, Mehta G, Mayani R,
Clark A, Lu J, Chen Y, Knowles J, Deelman E and Chen
T (2011) RseqFlow:
Workflows for RNA-seq data analysis. Bioinformatics. 27(18):
2598-2600.
9.
Xia C, Chen T, Furhman, and Sun F (2011) Accurate
Genome Relative Abundance Estimation for Shotgun Metagenomics
by Accommodating Read Assignment Ambiguities. PLOS One. 6(12), e27992. doi:10.1371/journal.pone.0027992.
10. Cho S, Kuo CC, and Chen T
(2011) MetaSEQ: De Novo Sequence Assembly of Short
Regions in Metagenomics. IEEE International
Workshop on Genomic Signal Processing. GSP 2011.
11. Souaiaia T, Frazer Z and Chen T (2011) ComB:
SNP Calling and Mapping Analysis for Color and Nucleotide Space Platforms.
Journal of Computational Biology. 18(6): 795-807.
13. Chen Y, Souaiaia T, and Chen
T (2009) PerM:
Efficient Mapping of Short Sequencing Reads with Periodic Full Sensitive Spaced
Seeds. Bioinformatics. 25(19):2514-21.
SNPs and Haplotypes
14. Chen Y and Chen
T (2010) An Integer Programming Approach for the Selection of Tag SNPs
using Multi-allelic LD. Communications in Information and Systems.
15. Jiang R,
Yang H, Kuo J CC, Sun F and Chen T.(2007) Sequence-based
prioritization of nonsynonymous single nucleotide
polymorphisms for the study of disease mutations. American Journal
of Human Genetics. 2007 Aug;81(2):346-60.
16.
Su, S, Kuo J CC, Chen T.(2007) Signal
Processing Techniques for SNP (Single Nucleotide Polymorphism) Data Analysis.
IEEE Signal Processing Magzine: Special Issue on
Signal Processing Methods in Genomics and Proteomics. 2007.
17.
Jiang R, Yang H, Sun F and Chen T.(2005)
Searching
for interpretable rules for disease mutations: A simulated annealing bump
hunting strategy. BMC Bioinformatics. 2006 Sep 19;7(1):417.
18.
Huang YT, Chao KM, and Chen T.(2005)
An
approximation algorithm for haplotype inference by maximum parsimony. Journal
of Computational Biology, Dec 2005;12(10):1261-74.
19. Huang YT,
Zhang K, Chen T and Chao KM.(2005) Approximation
algorithms for the selection of robust tag SNPs. BMC Bioinformatics,
2005, 6:263.
20.
Su S, Kuo CC and Chen T.(2005) Inference
of Missing SNPs and Haplotype Block Partitioning. Bioinformatics,
2005 May 1;21(9):2001-7.
21.
Zhang, K., Qin, Z., Chen, T., Liu, J., Waterman, MS, and
Sun, F. (2005) HapBlock: Haplotype Block Partitioning and Tag
SNP Selection Software Using a Set of Dynamic Programming Algorithms.
Bioinformatics, 2005 Jan 1;21(1):131-4.
22.
Zhang, K., Qin, Z., Liu, J., Chen, T.,
Waterman, MS, and Sun, F.(2004) Haplotype
Block Partitioning and Tag SNP Selection Using Genotype Data and Their
Applications to Association Studies. Genome
Res. 2004 May;14(5): 908-16.
23.
Zhang, K., Sun, F., Waterman, MS and Chen,
T.(2003) Dynamic programming algorithms
for partitioning sequence variation in human chromosomes. HERMIS
4:15-26, 2003.
24.
Zhang, K., Sun, F., Waterman, MS, Chen, T. (2003) Haplotype
block partition with limited resources and applications to human chromosome 21
haplotype data. American Journal of Human Genetics, 73:63-73,
2003.
25.
Zhang, K., Deng, M., Chen, T., Waterman, M., and Sun, F.(2002) A
dynamic programming approach for haplotype partitioning. The Proceeding
of National Academy of Sciences (PNAS), 99(11): 7335-9, May 28 2002.
Protein Interactions and Gene Expression
26. Jiang R, Chen
T, Sun FZ (2009) Bayesian
models and Gibbs sampling strategies for local graph alignment and network
motif identification in stochastic biological networks. Communications
in Systems and Information. Vol 9, No 4, pp
347-370.
27. Wang L, Sun
F and Chen T. (2008) Prioritizing
functional modules mediating genetic perturbations and their phenotypic
effects: a global strategy. Genome Biology. 9:R174, 2008.
28.
Pena-Castillo L. et al. (2008) A
critical assessment of Mus musculus
gene function prediction using integrated genomic evidence. Genome
Biol. 2008; 9 Suppl 1:S2.
29.
Jiang R, Tu Z, Chen
T and Sun F. (2006) Network
Motif Identification in Stochastic Networks. The Proceeding of
National Academy of Sciences (PNAS). 2006. vol 103 no 2 page 9404-9.
30.
Lee H, Deng M, Sun F and Chen T. (2006)
Inferring domain-domain interactions from multiple biological data sources.
BMC Bioinformatics. 2006 May 25;7(1):269.
31. Tu Z, Wang L, Arbeitman M, Chen T and Sun F. (2006) An
Integrative Approach for Causal Gene Identification and Gene Regulatory Pathway
Inference. Bioinformatics (ISMB 2006). Jul 15;22(14):e489-96.
32.
Tu Z, Wang L, Xu M, Zhou J, Chen T and Sun F. (2006) Further
understanding human disease genes by comparing with housekeeping genes and
other genes. 2006, BMC Genomics. 2006 Feb 21;7:31.
33.
Lee H, Tu Z, Deng M, Sun F and Chen
T. (2006) Diffusion
kernel based logistic regression models for protein function prediction.
OMICS: Integrative Biology. 2006 Spring;10(1):40-55.
34.
Lee H, Sun F and Chen T. (2005) Assessment
of the Reliability of Protein-Protein Interactions Using Protein Localization
and Gene Expression Data. BIOINFO 2005.
35.
Deng, M., Chen, T. and Sun, F. (2004) An
Integrative Analysis of Protein Function Prediction. Journal of
Computational Biology, 2004;11(2-3): 463-75.
36.
Deng, M., Tu, Z., Sun, F., and Chen,
T. (2004) Mapping
Gene Ontology to Proteins Based on Protein-protein Interaction Data. Bioinformatics,
Apr 12;20(6):895-902, 2004.
37.
Deng, M., Zhang, K., Mehta, S., Chen, T. and Sun, F.
(2003) Prediction
of protein function using protein-protein interaction data. Journal
of Computational Biology, 10(6): 947-960, 2003.
38.
Deng, M., Sun, F. and Chen, T. (2003) Assessment
of the reliability of protein-protein interactions and protein function
prediction. Pacific Symposium on Biocomputing. Page 140-51,
2003.
39.
Deng, M., Metah, S., Sun, F., and Chen,
T. (2002) Inferring
Domain-Domain Interactions from Protein-Protein Interactions. Genome
Research 12:1540-8, 2002.
40.
Chen, T., Filkov, V. and Skiena, S. (2001) Identifying
gene regulatory networks from experimental data. Journal of Parallel
Computing, 27(1-2), page 141-162, 2001.
41.
Chen, T., He, H. and Church, G.M. (1999) Modeling
Gene Expression with Differential Equations. Pacific Symposium on
Biocomputing (PSB99), Page 29-40, 1999.
Mass Spectrometry
42. Mo L, Wan Y,
Yang A and Chen T (2010) MSPEP: A spectral alignment
algorithm for the detection of post translational modifications. RECOMB
Satellite Conference on Computational Proteomics 2010.
43. Wan Y,
Cripps D, Thomas S, Campbell P, Ambulos N, Chen T,
Yang A. (2008) PhosphoScan: a probability-based
method for phosphorylation site prediction using MS2/MS3 pair information. J Proteome Res. 2008 Jul;7(7):2803-11. Epub 2008 Jun 13.
44.
Mo L, Dutta D,
Wan Y and Chen T (2007) MSNovo: A new dynamic programming algorithm for
de novo peptide sequencing. Analytical Chemistry 2007 Jul 1;79(13):4870-8.
45.
Dutta D. and Chen T (2007) Speeding up Tandem Mass Spectrometry Database
Search: Metric Embeddings and Fast Near Neighbor Search. Bioinformatics 2007; Mar 1;23(5):612-8.
46.
Wan Y and Chen T (2006) PepHMM: A hidden Markov model based scoring
function for tandem mass spectrometry. Analytical Chemistry.
2006 Jan 15;78(2):432-7.
47.
BA Soreghan, BW Lu, SN Thomas, K
Duff, EA Rakhmatulin, T Nikolskaya,
T Chen, & AJ. Yang (2005) Redox proteomic analysis of a PS1+APP
mouse model of Alzheimer’s disease. The Journal of Alzheimer’s
Disease. 2005 Dec;8(3):227-41.
48.
Lu, B. and Chen, T (2004) Algorithms for de novo
peptide sequencing via tandem mass spectrometry. Drug Discovery Today: BioSilico 2: 85-90, 2004.
49.
Lu, B. and Chen, T (2003) A
Suffix Tree Approach to the Interpretation of Tandem Mass Spectra: Applications
to Peptides of Nonspecific Digestion and Post-translational Modifications.
Bioinformatics Suppl. 2 (ECCB), Page 113-121, 2003.
50.
Lu, B. and Chen, T (2003) A
Suboptimal Algorithm for De novo Peptide Sequencing via Tandem Mass
Spectrometry. Journal of Computational Biology, 10(1):1-12,
2003.
51.
Chen, T., Jaffe, J. and Church, G.M. (2001) Algorithms
for Identifying Protein Cross-links via Tandem Mass Spectrometry, Journal
of Computational Biology, 8(6):571-583, 2001.
52.
Chen, T., Kao, M.Y., Tepel, M., Rush, J.,
and Church, G.M.(2001) A
Dynamic Programming Approach to De Novo Peptide Sequencing via Tandem Mass
Spectrometry. Journal of Computational Biology, 8(3): 325-337,
2001.
53.
Chen, T. Gene-Finding
via Tandem Mass Spectrometry.(2001) The
ACM-SIGACT Fifth Annual International Conference on Computational Molecular
Biology (RECOMB01), Page 85-92, 2001.
Chemical Informatics and Drug Screening
54. Guha R, Dutta D, Wild
DJ, Chen T(2007) Counting Clusters Using R-NN Curves. J Chem Inf
Model. 2007 Jul-Aug;47(4):1308-18. Epub 2007 Jun 30.
55.
Dutta
D, Guha R, Wild D and Chen T(2007)
Ensemble Feature Selection: Consistent Descriptor Subsets for Multiple QSAR Models.
ACS J. Chem. Inf. Model. 2007. May-Jun;47(3):989-97.
56.
Guha R, Dutta D, Jurs P. and Chen T(2006)
R-NN
Curves: An Intuitive Approach to Outlier Detection Using a Distance Based
Method. ACS J. Chem. Inf. Model. 2006. Jul-Aug;46(4):1713-22.
57.
Dutta D, Guha R, Jurs P. and Chen T(2006)
Local
Lazy Regression: Making Use of the Neighborhood to Improve QSAR Predictions.
ACS J. Chem. Inf. Model., 2006. Jul-Aug;46(4):1836-47.
58.
Dutta D, Guha R, Jurs P. and Chen T(2006)
Scalable
Partitioning and Exploration of Chemical Spaces Using Geometric Hashing.
ACS J. Chem. Inf. Model., 2006. Jan-Feb;46(1):321-33.
Books and Book Chapters
59.
Sun FZ, Chen T, Deng MH, Lee HJ, Tu
ZD (2006) Data integration for the study of protein interactions. In Rudy
Guerra and David Allison: Meta-analysis and Combining Information in Genetics,
Chapman and Hall.
60.
Huang, Y.-T., Zhang, K., Chen, T., and Chao, K. -M. (2006)
“Approximation Algorithms for the Selection of Robust Tag SNPs,” a
chapter of the book “Handbook of Approximation Algorithms and Metaheuristics," edited by Teofilo
F. Gonzalez (University of California, Santa Barbara), to be published by
Chapman & Hall/CRC Press, USA.
61.
BW Lu, BA Soreghan, SN Thomas, T
Chen, & AJ Yang. (2005) Proteomics data management and visualization. Book
chapter.
62.
Borchers, C., Chen,
T. and Neamati, N. Book Chapter: Application of
Proteomics in Biological Sciences. Molecular Carcinogenesis. Editor:
Joseph R. Landolph's and David Warshawsky. CRC Press, 2003.
63.
Chen, T. and Waterman, M. Book Chapter: Dynamic Programming.
Nature Encyclopedia of Human Genome, Nature Publishing, 2003.
Other Works
64. Jia L, Berman
BP, Jariwala U, Yan X, Cogan JP, Walters A, Chen T,
Buchanan G, Frenkel B, Coetzee GA. (2008) Genomic androgen
receptor-occupied regions with different functions, defined by histone
acetylation, coregulators and transcriptional
capacity. PLoS ONE. 2008;3(11):e3645.
Epub 2008 Nov 10
65.
Smith E, Meyerrose
TE, Kohler T, Namdar-Attar M, Bab N, Lahat O, Noh T, Li J, Karaman MW,
Hacia JG, Chen T, Nolta JA,
Muller R, Bab I, Frenkel B.(2005)
Leaky
ribosomal scanning in mammalian genomes: Physiological consequences of histone
H4 alternative translation. Nucleic Acid Research. 2005 Mar 1;33(4):1298-308.
66.
Wyrick, J. J., Aparicio, J. G., Chen, T., Barnett, J. D., Jennings, E. G.,
Young, R. A., Bell, S. P., and Aparicio, O. M.(2001) Genome-Wide
Location Analysis of ORC and MCM Proteins: High Resolution Mapping of
Replication Origins Reveals Novel Origin Classes in Saccharomyces cerevisiae. Science, 2357-2360, Dec 14,
2001.
67.
Chen, T. and Skiena, S.(2000) A
Case Study in Genome-Level Fragment Assembly. Bioinformatics
2000 16:494-500.
68.
Chen, T. and Kao, M.Y. (1999) On
the Informational Asymmetry between Upper and Lower Bounds for Ultrametric Evolutionary Trees. The 7th
Annual European Symposium on Algorithms (ESA’99), Page 248-256, 1999.
LNCS, Lecture Notes in Computer Science, Springer-Verlag.
69.
Chen, T. and Zhang, M.Q.(1998) Pombe: A Fission Yeast gene-finding and
exon-intron structure prediction system. Yeast, Vol. 14:
701-710, 1998.
70.
Chen, T. and Skiena, S.(1997) Trie-based data structures for fragment assembly.
The Eighth Symposium on Combinatorial Pattern Matching (CPM97), page
206-223, 1997.
71.
Chen, T. and Skiena, S.(1996) Sorting
with fixed-length reversals. Journal of Discrete Applied Mathematics,
Special Volume on Computational Molecular Biology, page 269-296, vol.71,
December 5 1996.
·
PerM (http://code.google.com/p/perm/): a read-mapping software based on
periodic spaced seeds for both Illumina and SOLiD sequencing data.
·
Clippers (http://code.google.com/p/clippers/): a
sister gap-mapping program of PerM, which is designed to map
75-bp or longer Illumina reads with one gap plus multiple substitutions. Clippers has been used to find novel spliced junctions and
junctions of structural variations.
·
ComB (http://code.google.com/p/ComB): a Bayesian
model for SNP-calling for both Illumina and SOLiD sequencing
data, which iteratively maps reads to the genome, calls SNPs, and updates the
genome sequences. ComB has been used to analyze allele specific gene
expression, and RNA-editing sites.
·
WeaV(http://code.google.com/p/weav-assembler/):
a de novo assembly program for both genome and RNA.
·
CROP(http://code.google.com/p/crop-tingchenlab/): an supervised Bayesian clustering tool for Metagenomics studies, which clusters 16S
rRNA sequences into Operational
Taxonomic Units (OTU).
·
RseqFlow (http://genomics.iss.edu/rnaseq): an RNA-seq
data analysis workflow, which uses Pegasus Workflow Management System
to develop and manage workflow execution. RseqFlow has been applied to analyze
the RNA-seq data sets generated from the NIHM funded human brain transcriptome
atlas project.
·
Fade (http://code.google.com/p/fade): a DNA methylation calling program.
·
SInBaD(http://tingchenlab.cmb.usc.edu/sinbad/): a database for human functional variant prediction in promoter, coding, and intron
regions.
o USC High Performance Computing Committee, 2007-present.
o Graduate Student Advisor, PhD program in Computational Biology and Bioinformatics, 2006-present.
o USC College Biology Undergraduate Curriculum Committee, 2007-2008, 2011-present
o USC Clinical Translational Science Institute (CTSI): Computational Biology Advisory Committee, 2007-present.
o USC College Faculty Council, 2005-2006.
o Faculty Recruit Committee, 2006-present.
o Current PhD students (4)
Misagh Bagheria,
Zohreh Irannia,
Haifeng Chen,
Feng Zeng
o Former Postdocs (5)
Ying Wang (Associate Professor, Department of Automation, Xiamen University)
Rui Jiang (Associate Professor, Department of Automation, Tsinghua University)
Minghua Deng (Professor, Department of Mathematics, Peking University)
Debo Dutta (Senior Scientist, Cisco)
Lei Zhuge (Countrywide)
o Former Graduated PhD students (12)
Hyun-Ju Lee (Assistiant Professor, Department of Computer Science, Gwangju Inst. Of Tech, Korea),
Hua Yang (Deputy Director, China Banking Regulatory Commission)
Bingwen Lu (Pfizer),
Shipra Metah,
Yunhu Wan (Consultant, National Cancer Institute),
Shih-Chieh Su (Analytic Scientist, Fair Isaac Co),
Lijuan Mo (CEO, Archiwood)
Yangho Chen (Microsoft)
Tade Souaiaia (USC)
Kjong Lehmman,
Sungje Cho,
Xiaolin Hao