Jagath C. Rajapakse

Professor of Computer Engineering

Director, BioInformatics Research Center

Nanyang Technological University
50 Nanyang Avenue
Singapore 639798

Email: asjagath[at]ntu.edu.sg

jagath[at]mit.edu

Tel: +65 67905802/67906608

Fax: +65 67926559/63162780

Professor Rajapakse is with the School of Computer Engineering and the Director of BioInformatics Research Center, Nanyang Technological University (NTU). He is a Visiting Professor to the Department of Biological Engineering, Massachusetts Institute of Technology (MIT). He received his First Class (Hons) Bachelor degree in electronic and telecommunication engineering from the University of Moratuwa (Sri Lanka). He began his post-graduate studies under the Fulbright Scholarship at the University of Buffalo (USA) where he received Master and Ph.D. degrees in electrical and computer engineering. Before joining NTU, he was a Visiting Fellow at the National Institute of Mental Health (USA) and a Visiting Scientist at the Max-Planck-Institute of Brain and Cognitive Sciences (Germany).

His research interests are in the areas of neuroinformatics and bioinformatics. Professor Rajapakse has pioneered several techniques for analysis of anatomical and functional MR images. His contributions include extending the Bayesian framework for segmentation of brain tissues, detection of brain activation, and modeling the brain connectivity. His proposal to approximate hemodynamic response function with a Gaussian led to the estimation of hemodynamic parameters of human brain. Recently, his team was first to develop techniques to model brain connectivity in an exploratory manner, by performing functional MR experiments, and to introduce constrained Independent Component Analysis (cICA) as a technique for semi-blind signal processing. His team is investigating brain connectivity patterns underlying higher-order brain functions such as language and memory, and brain disease such as Parkinson's disease.

His interest in systems and synthetic biology is to develop in silico techniques to identify key targets in biological pathways. His research is centered on gene selection, building gene regulatory networks, fusion of protein-interactions, and identifying key molecules and core networks of pathways. In order to understand cell signaling pathways, his team is developing techniques to identify cells, protein localizations, and spatiotemporal changes of cell morphologies from tissue images obtained in microscopy and high content screening.

Professor Rajapakse has made several fundamental contributions in his area of research and was listed among the most cited scientists. He has published over 200 peer-reviewed international conference and journal papers, and book chapters. He has edited six books and four conference proceedings. Professor Rajapakse serves as an Associate Editor for the IEEE Transactions on Medical Imaging, the IEEE Transactions on Computational Biology and Bioinformatics, and the IEEE Transactions on Neural Networks, and in editorial boards of several other journals. He is a co-founder of IAPR Technical Committee (TC-20) on Pattern Recognition for Bioinformatics and PRIB conference series. He was the General Chair of PRIB 2007 Singapore, General Co-Chair of CIBCB 2007 Hawaii, Program Chair/Co-Chair of ICONIP 2002 Singapore, PRIB 2006 Hong Kong, EvoBIO 2007 Valencia, PRIB 2008 Melbourne, and PRIB 2009 Sheffield, and Special Session Chair of WCCI 2008 Hong Kong.

His research projects have been funded by NTU, Ministry of Education (MOE), Science and Engineering Research Council (SERC) and BioMedical Research Council (BMRC) of the Agency of Science and Technology Research (ASTAR), National Grid Office (NGO), Singapore-MIT Alliance (SMA), Singapore-MIT Alliance for Research and Technology (SMART) Center, and Hewlett-Packard, Singapore, and Sun Microsystems, USA.

Bio Sketch

• Teaching

o BI6103: Computational Biology

o SMA 5303/MIT 15.077: Statistical learning and data mining in bioinformatics

o SMA 5301: Perspectives of Computational and Systems Biology

o Previously taught courses

• University Services

o BioInformatics Research Centre (BIRC)

o R & D Committee, School of Computer Engineering (SCE)

o Computation and Systems Biology (CSB) program, SMA

o Committee on implementation of Blue Ribbon Commission recommendations, College of Engineering

o SMART Center

· Research

o Grants

o Graduate students

• Team
• Software (kindly cite the publication if the software contributes to your research) : 
• AMAP ( IEEE Transactions on Medical Imaging, Vol. 16, No. 2, 1997, pp. 176-186)  
• BMAP (Image &Vision Computing, Vol. 16, No. 3, 1998, pp. 165-180)
• Benchmarking of MR tissue segmentation algorithms

o Talks

· Selected Publications

• P. Mundra and J. C. Rajapakse, “SVM-RFE with MRMR filter for gene selection,” IEEE Transactions on Nanobiosciences (accepted)
• M. N. Nguyen, J. M. Zurada, and J. C. Rajapakse, “Towards better understanding of protein secondary structure: extracting prediction rules,” IEEE Transactions on Computational Biology and Bioinformatics, (accepted)
• M. Veronika, J. Evans, P. Matsudaira, R. Welsch, and J. C. Rajapakse, “Subpopulation analysis based on temporal features of high content images,” BMC Bioinformatics (in press)
• I. Chaturvedi and J. C. Rajapakse, “Detecting robust time-delayed regulation in Mycobacterium tuberculosis,” BMC Genomics, (in press)
• M. N. Nguyen, J. Ma, G. B. Fogel, J. C. Rajapakse, “Dicodon usage for classification of genes,” Biosystems, 98 (1), 2009, pp. 1-6
• J. C. Rajapakse, “Computational techniques: pattern discovery in bioinformatics,” IEEE Engineering in Medicine and Biology, Vol. 28, Issue 4, July 2009, pp. 19-24
• J. C. Rajapakse, Pooja, C. Chen, and S-Y Ho, “Comparative genomic workflow: discovery of conserved noncoding DNA patterns,” IEEE Engineering in Medicine and Biology, Vol. 28, Issue 4, July 2009, pp. 16-18
• J. Cheng and J. C. Rajapakse, “Segmentation of clustered nuclei with shape markers and marking function,” IEEE Transactions on Biomedical Engineering, Vol. 56, No. 3, March 2009, pp. 741-748
• Y. Zhang and J. C. Rajapakse (Eds.), Machine Learning in Bioinformatics, John Wiley and Sons Inc., 2009
• J. Ma, M. N. Nguyen, and J. C. Rajapakse, “Gene classification using codon usage pattern analysis and support vector machines,” IEEE Transactions on Computational Biology and Bioinformatics, Vol. 6, No. 1, Jan-March 2009, pp. 134-143
• B. Zheng and J. C. Rajapakse, “Time-efficient diffusion-tensor MRI acquisition parameters for robust estimation of fibre tracts,” Journal of Signal Processing Systems,” 54 (1-3), pp. 25-31, 2009
• J. Zhou and J. C. Rajapakse, “Fuzzy approach to incorporate hemodynamic variability and contextual information for detection of brain activation,” Neurocomputing, 71 (16-18), pp. 3184 – 3192, 2008
• J. C. Rajapakse, W. Yang, X. Zheng, and J. Zhou, “Probabilistic framework for brain connectivity from functional MR images,” IEEE Transactions on Medical Imaging, Vol. 27, No. 6, pp. 825-833, 2008
• J. C. Rajapakse and J. Zhou, “Modeling effective brain connectivity with dynamic Bayesian networks,” NeuroImage, Vol. 37, Issue 3, Sept 2007, pp. 749-760
• N. Nguyen and J. C. Rajapakse, “Two stage support vector machines for protein secondary structure prediction,” International Journal of Data Mining and Bioinformatics, Vol. 1, No. 3, pp. 248-269, January 2007
• W. Lu and J. C. Rajapakse, “ICA with Reference,” Neurocomputing, 69. pp. 2244 – 2257, Oct 2006
• X. Zheng and J. C. Rajapakse, “Learning functional structure from fMR images,” NeuroImage, Vol. 31, No. 4, pp. 1601-1613, July 2006
• Y. Wang and J. C. Rajapakse, “Contextual modeling of functional MR images with conditional random fields,” IEEE Transactions on Medical Imaging, Vol. 25, No. 6, pp. 804-812, June 2006
• M. N. Nguyen and J. C. Rajapakse, “Two-stage support vector regression approach for predicting accessible surface areas of amino acids,” PROTIENS: Structure, Function, and Bioinformatics, 63: 542-550, May 2006
• J. C. Rajapakse, C. L. Tan, X. Zheng, S. Mukhopadyay, and K. Yang, “Exploratory analysis of brain connectivity with ICA,” IEEE Engineering in Medicine and Biology Magazine, March/April Issue, Vol. 25, No. 2, 2006, pp. 102-111
• L. S. Ho, and J. C. Rajapakse, “Input encoding method for identifying transcription start sites in RNA polymerase II promoters by neural networks,” Soft Computing, Vol. 10, No. 4, pp. 331-337, February 2006
• R. G. N. Meegama and J. C. Rajapakse, “NURBS-based visualization of age-related diversity in cortical morphology,” Journal of Visualization, Vol. 9, No. 1, 2006, pp. 9-11, January 2006
• A. R. Omondi and J. C. Rajapakse (Eds.) FPGA Implementations of Neural Networks, Springer-Verlag, 2006, Approx 365p, Hardcover, ISBN: 0-387-28485-0
• J. Zhou and J. C. Rajapakse, “Segmentation of subcortical brain structures using fuzzy templates,” NeuroImage, Vol. 28, No. 4, Dec. 2005, pp. 927-936
• W. W. P. Tham, S. J. R. Liow, J. C. Rajapakse, C. L. Tan, S. E. S. Ng, W. E. H. Lim, and L. G. Ho, “Phonological processing in Chinese-English bilingual biscriptals: an fMRI study, “, NeuroImage, Vol. 28, No. 3, Nov. 2005, pp. 579-587
• J. C. Rajapakse, K.-B. Duan, and W. K. Yeo, “Proteomic cancer classification with mass spectra data”, American Journal of Pharmacology, 5 (5), October 2005, pp. 228-234
• K.-B. Duan, J. C. Rajapakse, H. Wang, and F. Azuaje, “Multiple SVM-RFE for gene selection in cancer classification witn expression data,” IEEE Transactions on Nanobioscience, Vol. 4, No. 3, September 2005, pp. 228-234.
• J. C. Rajapakse and L. S. Ho, "Markov encoding for detecting signals in genomic sequences,", IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 2, No. 2, April-June, 2005, pp. 131-142
• M. N. Nguyen and J. C. Rajapakse, “Prediction of protein relative solvent accessibility with a two-stage SVM approach,” PROTIENS: Structure, Function, and Bioinformatics, Vol. 59, Issue 1, April 2005, pp. 30-37
• W. Lu and J. C. Rajapakse, “Approach and applications of constrained ICA”, IEEE Transactions on Neural Networks, Vol. 16, No. 1, January, 2005, pp. 203-212

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Last updated on 06/05/2009