Jagath C. Rajapakse

发表

Non independent strategies for blind source separation in functional MRI

Krzysztof Siwek, Andrzej Cichocki, Jagath C. Rajapakse, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Neural Information Processing: Research and Development

Jagath C. Rajapakse, Lipo Wang, 2004 .

Gene Classification Using Codon Usage Patterns and SVMs

Jagath C. Rajapakse, Jianmin Ma, Minh Ngoc Nguyen, 2005, CIBCB.

Protein-Protein Interface Residue Prediction with SVM Using Evolutionary Profiles and Accessible Surface Areas

Jagath C. Rajapakse, Minh Ngoc Nguyen, M. N. Nguyen, 2006, 2006 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology.

Hierarchical neural architecture for visual pattern recognition and reconstruction

Raj S. Acharya, Jagath C. Rajapakse, 1990, Other Conferences.

Features for cells and nuclei classification

Song Liu, Jagath C. Rajapakse, Piyushkumar A. Mundra, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Bayesian tissue segmentation of multispectral brain images

Jagath C. Rajapakse, Choong Leong Tan, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

MultiDCoX: Multi-factor analysis of differential co-expression

Jagath C. Rajapakse, Herty Liany, R. Krishna Murthy Karuturi, 2017, BMC Bioinformatics.

ICA with Reference

Wei Lu, Jagath C. Rajapakse, W. Lu, 2006, Neurocomputing.

Pattern Recognition in Bioinformatics, International Workshop, PRIB 2006, Hong Kong, China, August 20, 2006, Proceedings

Limsoon Wong, Jagath C. Rajapakse, Raj Acharya, 2006, PRIB.

Two-stage support vector machines to protein relative solvent accessibility prediction

Jagath C. Rajapakse, Minh Ngoc Nguyen, M. N. Nguyen, 2004, 2004 Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

Statistical analysis of drug treated cell morphologies from HCS image data

Roy E. Welsch, Jagath C. Rajapakse, James G. Evans, 2008 .

Dynamically weighted time-delay neural networks for functional approximation

Jagath C. Rajapakse, V. Venkatraman, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

DISCRIMINATIVE FRAMEWORK OF NEURAL ACTIVATION ANALYSIS WITH fMRI

Jagath C. Rajapakse, Yang Wang, 2011 .

A variant of SVM-RFE for gene selection in cancer classification with expression data

Jagath C. Rajapakse, Kaibo Duan, Jagath Rajapakse, 2004, 2004 Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

Graphical Models for Brain Connectivity from Functional

Jagath C. Rajapakse, Xuebin Zheng, 2004 .

EXTRACTING TASK-RELATED COMPONENTS IN FUNCTIONAL MRI

Wei Lu, Jagath C. Rajapakse, Wei Lu, 2001 .

Neuronal and Hemodynamic Events from fMRI Time-Series

Frithjof Kruggel, Jagath C. Rajapakse, D. Yves von Cramon, 1998, J. Adv. Comput. Intell. Intell. Informatics.

Denoising of functional MRI using ICA

Jagath C. Rajapakse, Kanyan Yang, Jagath Rajapakse, 2003, 3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the.

MultiDCoX: Multi-factor analysis of differential co-expression

Karuturi R. Krishna Murthy, Jagath C. Rajapakse, Herty Liany, 2017, BMC Bioinformatics.

Building gene networks with time-delayed regulations

Jagath C. Rajapakse, Iti Chaturvedi, 2010, Pattern Recognit. Lett..

Genetic approach to biosequence alignment (GABA)

Jagath C. Rajapakse, I. Faleel, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Discovering Power Laws in Entity Length pdf

Erik Cambria, Jagath C. Rajapakse, Xiaoshi Zhong, 2018, ArXiv.

Phonological Processing in Chinese–english Bilingual Biscriptals: an Fmri Study

Jagath C. Rajapakse, Wendy W. P. Tham, Susan J. Rickard Liow, 2005 .

Eliminating indeterminacyin ICA

Wei Lu, Jagath C. Rajapakse, Wei Lu, 2003 .

An exploratory approach to modelling effective connectivity

Jagath C. Rajapakse, Kanyan Yang, Jagath Rajapakse, 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

Extracting rate changes in transcriptional regulation from MEDLINE abstracts

Kuiyu Chang, Guangxia Li, Jagath C. Rajapakse, 2014, BMC Bioinformatics.

Pattern Recognition in Bioinformatics: 9th IAPR International Conference, PRIB 2014, Stockholm, Sweden, August 21-23, 2014. Proceedings

Elena Marchiori, Alioune Ngom, Matteo Comin, 2014 .

NURBS-Based Segmentation of the Brain in Medical Images

Ravinda G. N. Meegama, Jagath C. Rajapakse, R. Meegama, 2003, Int. J. Pattern Recognit. Artif. Intell..

Splice site detection using a combination of Markov Model and neural network

Saman K. Halgamuge, Jagath C. Rajapakse, Abdul Baten, 2005 .

Pattern Recognition in Bioinformatics: An Introduction

Limsoon Wong, Raj Acharya, Jagath C. Rajapakse, 2006, PRIB.

Deep neural network ensemble by data augmentation and bagging for skin lesion classification pdf

Jagath C. Rajapakse, Manik Goyal, Jagath Rajapakse, 2018, ArXiv.

Subspace blind extraction by less-complete ICA

Jagath C. Rajapakse, Wei Lu, W. Lu, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Support vectors based correlation coefficient for gene and sample selection in cancer classification

Jagath C. Rajapakse, Piyushkumar A. Mundra, P. Mundra, 2010, 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

Evolutionary approach to ICA-R

Jacek M. Zurada, Swathi Kavuri Sri, Jagath C. Rajapakse, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Estimation of the population of neutrophils induced to differentiate from the MPRO mouse promyelocytic cell line

Roy E. Welsch, Jagath C. Rajapakse, Vincent T. K. Chow, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Segmentation of pathological features in MRI brain datasets

Frithjof Kruggel, Jagath C. Rajapakse, X. Descombes, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

NURBS-based analysis of gender-related variability of the human brain surface

Ravinda G. N. Meegama, Jagath C. Rajapakse, Loi Sy Ho, 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

Predicting Missing and Spurious Protein-Protein Interactions Using Graph Embeddings on GO Annotation Graph

Jagath C. Rajapakse, Xiaoshi Zhong, Xiaoshi Zhong, 2019, 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Decoding Task States by Spotting Salient Patterns at Time Points and Brain Regions

Jagath C. Rajapakse, Sukrit Gupta, Yi Hao Chan, 2020, MLCN/RNO-AI@MICCAI.

Comparison of Human and Mouse Pseudogenes

Pooja, Jagath C. Rajapakse, Pooja, 2007, 2007 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology.

Fuzzy approach to incorporate hemodynamic variability and contextual information for detection of brain activation

Juan Zhou, Jagath C. Rajapakse, Juan Zhou, 2008, Neurocomputing.

Image acquisition and processing techniques in neuroscience

Frithjof Kruggel, Jagath C. Rajapakse, 2000 .

Markov encoding for detecting signals in genomic sequences

Jagath C. Rajapakse, Loi Sy Ho, Jagath Rajapakse, 2005, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Integration of Epigenetic Data in Bayesian Network Modeling of Gene Regulatory Network

Jagath C. Rajapakse, Jie Zheng, Iti Chaturvedi, 2011, PRIB.

Multiclass Gene Selection Using Pareto-Fronts

Jagath C. Rajapakse, Piyushkumar A. Mundra, P. Mundra, 2013, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Grid-Enabled BLASTZ: Application to Comparative Genomics

Jagath C. Rajapakse, Chunxi Chen, Jagath Rajapakse, 2007, J. VLSI Signal Process..

Gene and sample selection for cancer classification with support vectors based t-statistic

Jagath C. Rajapakse, Piyushkumar A. Mundra, P. Mundra, 2010, Neurocomputing.

Segmentation of Clustered Nuclei With Shape Markers and Marking Function

Jagath C. Rajapakse, Jierong Cheng, Jierong Cheng, 2009, IEEE Transactions on Biomedical Engineering.

Fusing gene expressions and transitive protein-protein interactions for inference of gene regulatory networks

Jagath C. Rajapakse, Wenting Liu, Wenting Liu, 2019, BMC Systems Biology.

Constrained Independent Component Analysis

Wei Lu, Jagath C. Rajapakse, Wei Lu, 2000, NIPS.

Locality regularized sparse subspace clustering with application to cortex parcellation on resting fMRI

Jagath C. Rajapakse, Shaohua Li, Xiuchao Sui, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

CUDAGRN: Parallel Speedup of Inferring Large Gene Regulatory Networks from Expression Data Using Random Forest

Rui Fan, Jagath C. Rajapakse, Jie Zheng, 2014, PRIB.

Contextual modeling of functional MR images with conditional random fields

Yang Wang, Jagath C. Rajapakse, Jagath Rajapakse, 2006, IEEE Transactions on Medical Imaging.

Identifying Cells in Histopathological Images

Jagath C. Rajapakse, Jierong Cheng, Merlin Veronika, 2010, ICPR Contests.

Nodal degree distributions of resting-state functional brain modules

Jagath C. Rajapakse, Sukrit Gupta, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

Intensity normalization of two-photon microscopy images for liver fibrosis analysis

Jagath C. Rajapakse, Peter T. C. So, Vijay Raj Singh, 2011, BiOS.

Approach and applications of constrained ICA

Wei Lu, Jagath C. Rajapakse, Jagath Rajapakse, 2005, IEEE Transactions on Neural Networks.

A NURBS-Based Technique for the Segmentation of Medical Images

Ravinda G. N. Meegama, Jagath C. Rajapakse, 2002, ICVGIP.

Graphical approach for motif recognition in DNA sequences

Xiao Yang, Jagath C. Rajapakse, X. Yang, 2004, 2004 Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

Extracting decision rules in prediction of protein secondary structure

Jacek M. Zurada, Jagath C. Rajapakse, Minh Ngoc Nguyen, 2008, 2008 8th IEEE International Conference on BioInformatics and BioEngineering.

Performance Comparison of ICA Neural Networks Separating Audio Signals

Ian McLoughlin, Jagath C. Rajapakse, V. Loh, 1999 .

Iterative consensus spectral clustering improves detection of subject and group level brain functional modules

Jagath C. Rajapakse, Sukrit Gupta, Sukrit Gupta, 2020, Scientific Reports.

Time Efficient DT-MRI Acquisition Parameters for Robust Estimation of Fiber Tracts

Jagath C. Rajapakse, Bo Zheng, 2009, J. Signal Process. Syst..

Di-codon usage for classification of genes

Jagath C. Rajapakse, Gary B. Fogel, Minh Ngoc Nguyen, 2009, Biosyst..

Proceedings of the 9th IAPR International Conference on Pattern Recognition in Bioinformatics - Volume 8626

Elena Marchiori, Alioune Ngom, Matteo Comin, 2014 .

Neuronal and Hemodynamic Responses from Functional MRI Time-Series: A Computational Model

Frithjof Kruggel, Jagath C. Rajapakse, 1997, ICONIP.

Automated Scoring System for Liver Fibrosis Diagnosis with Second Harmonic Generation Microscopy

Hanry Yu, Jagath C. Rajapakse, Shuoyu Xu, 2010, Aust. J. Intell. Inf. Process. Syst..

Inferring Time-Delayed Gene Regulatory Networks Using Cross-Correlation and Sparse Regression

Roy E. Welsch, Mahesan Niranjan, Jagath C. Rajapakse, 2013, ISBRA.

NURBS-based visualization of age-related diversity in cortical morphology

Ravinda G. N. Meegama, Jagath C. Rajapakse, R. Meegama, 2006, J. Vis..

Inferring Gene Regulatory Networks from Time-Series Expressions Using Random Forests Ensemble

Jagath C. Rajapakse, Jie Zheng, Piyushkumar A. Mundra, 2013, PRIB.

SVM-RFE peak selection for cancer classification with mass spectrometry data

Jagath C. Rajapakse, Kaibo Duan, Jagath Rajapakse, 2005, APBC.

Eliminating indeterminacy in ICA

Wei Lu, Jagath C. Rajapakse, Wei Lu, 2003, Neurocomputing.

Fuzzy neural approach for segmentation of subcortical structures from MR head scans

Li Shan, Jagath C. Rajapakse, Shi Jian, 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

Fully Automated Peeling Technique For T1-Weighted, High-Quality Mr Head Scans

Ravinda G. N. Meegama, Jagath C. Rajapakse, R. Meegama, 2004, Int. J. Image Graph..

Emerging region segmentation

Jagath C. Rajapakse, 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

Decoding Brain Functional Connectivity Implicated in AD and MCI

Jagath C. Rajapakse, Sukrit Gupta, Yi Hao Chan, 2019, MICCAI.

Obtaining leaner deep neural networks for decoding brain functional connectome in a single shot

Jagath C. Rajapakse, Sukrit Gupta, Yi Hao Chan, 2020, bioRxiv.

Automated scoring of liver fibrosis through combined features from different collagen groups

Roy E. Welsch, Hanry Yu, Jagath C. Rajapakse, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Learning effective brain connectivity with dynamic Bayesian networks

Juan Zhou, Jagath C. Rajapakse, Juan Zhou, 2007, NeuroImage.

Proceedings of the 2nd IAPR international conference on Pattern recognition in bioinformatics

Bertil Schmidt, Jagath C. Rajapakse, Gwenn Volkert, 2006 .

Editorial for special issue on “Soft Computing for Bioinformatics and Medical Informatics”

David W. Corne, Lipo Wang, Jagath C. Rajapakse, 2006, Soft Computing - A Fusion of Foundations, Methodologies and Applications.

One-Versus-One and One-Versus-All Multiclass SVM-RFE for Gene Selection in Cancer Classification

Jagath C. Rajapakse, Minh Ngoc Nguyen, Kaibo Duan, 2007, EvoBIO.

Graphical Approach to Weak Motif Recognition in Noisy Data Sets

Jagath C. Rajapakse, Loi Sy Ho, 2006, PRIB.

Regularization approach to multisensor reconstruction

Raj S. Acharya, Jagath C. Rajapakse, R. Acharya, 1993, Other Conferences.

Segmentation of MR images with intensity inhomogeneities

Frithjof Kruggel, Jagath C. Rajapakse, J. Rajapakse, 1998, Image Vis. Comput..

Gene regulatory networks with variable-order dynamic Bayesian networks

Jagath C. Rajapakse, Iti Chaturvedi, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

International program committee

Akinori Sarai, Jagath C. Rajapakse, Maria Samsonova, 2011, 2011 Sixth International Conference on Digital Information Management.

Emerging segmentation of neuroanatomical structures in magnetic resonance images

Jagath C. Rajapakse, Choong Leong Tan, J. Rajapakse, 1999, ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378).

Boundary based movement correction of functional MR data using a genetic algorithm

Jagath C. Rajapakse, Guojun Bao, 2000, ESANN.

Validation of Gene Regulatory Networks from Protein-Protein Interaction Data: Application to Cell-Cycle Regulation

Jagath C. Rajapakse, Meena Kishore Sakharkar, Iti Chaturvedi, 2007, PRIB.

Soft computing approach to brain structure segmentation

Li Shan, Shi Jian, Jagath C. Rajapakse, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Tissue segmentation of multi-channel brain images with inhomogeneity correction

Jagath C. Rajapakse, Choong Leong Tan, 2003, 3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the.

Decoding brain functional connectivity implicated in AD and MCI

Jagath C. Rajapakse, Sukrit Gupta, Yi Hao Chan, 2019, bioRxiv.

RecMotif: a novel fast algorithm for weak motif discovery

Wen-Jing Hsu, Malcolm Yoke-Hean Low, Jagath C. Rajapakse, 2010, BMC Bioinformatics.

Combining GOR techniques with support vector machines for protein secondary structure prediction

Jagath C. Rajapakse, Minh Ngoc Nguyen, Loi Sy Ho, 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

Automatic segmentation of skin lesions using deep learning pdf

Jagath C. Rajapakse, Joshua Peter Ebenezer, 2018, ArXiv.

Two-Stage Multi-Class Support Vector Machines to Protein Secondary Structure Prediction

Jagath C. Rajapakse, Minh Ngoc Nguyen, M. N. Nguyen, 2004, Pacific Symposium on Biocomputing.

Guest Editors' Introduction to the Special Section: Computational Intelligence Approaches in Computational Biology and Bioinformatics

Jagath C. Rajapakse, Gary B. Fogel, Yan-Qing Zhang, 2007, TCBB.

Computational techniques and pattern recognition

Jagath C. Rajapakse, 2009 .

Gene Regulatory Networks from Gene Ontology

Kuiyu Chang, Jung-jae Kim, Jagath C. Rajapakse, 2013, ISBRA.

Functional MR image registration using a genetic algorithm

Jagath C. Rajapakse, B. Guojun, 1999, ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378).

Inferring neutral evolution from Parkinson's disease genes

Jagath C. Rajapakse, Gavyn Pang, G.W.L. Pang, 2004, 2004 Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

A neural network for undercomplete independent component analysis

Lu Wei, Jagath C. Rajapakse, Jagath Rajapakse, 2000, ESANN.

Joint Tracking of Cell Morphology and Motion

Jagath C. Rajapakse, Jierong Cheng, Sohail Ahmed, 2009, PRIB.

Functional homogeneity and specificity of topological modules in human proteome

Jagath C. Rajapakse, Rama Kaalia, 2018, BMC Bioinformatics.

Bayesian Approach to Segmentation of Statistical

Jagath C. Rajapakse, Student Member, Jayasanka Piyaratna, 2001 .

Complex ICA-R

Jagath C. Rajapakse, Wenda Chen, Jagath Rajapakse, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Multimodality fusion of physiological images using regularization theory and deformable models

Raj S. Acharya, Jagath C. Rajapakse, Richard M. Wasserman, 1994, Medical Imaging.

Fitting networks models for functional brain connectivity

Jagath C. Rajapakse, Sukrit Gupta, Xiuchao Sui, 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

Augmenting HMM with neural network for finding gene structure

Jagath C. Rajapakse, Minh Ngoc Nguyen, Loi Sy Ho, 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

Prediction of Protein Secondary Structure with two-stage multi-class SVMs

Jagath C. Rajapakse, Minh Ngoc Nguyen, M. N. Nguyen, 2007, Int. J. Data Min. Bioinform..

Syntactic Approach to Predict Membrane Spanning Regions of Transmembrane Proteins

Jagath C. Rajapakse, Koliya Pulasinghe, 2005, EvoWorkshops.

Di-codon Usage for Gene Classification

Jagath C. Rajapakse, Gary B. Fogel, Jianmin Ma, 2009, PRIB.

Statistical approach to segmentation of single-channel cerebral MR images

Jagath C. Rajapakse, Jay N. Giedd, Judith L. Rapoport, 1997, IEEE Transactions on Medical Imaging.

Quantification of Cytoskeletal Protein Localization from High-Content Images

Roy E. Welsch, Jagath C. Rajapakse, Paul Matsudaira, 2010, PRIB.

Color channel encoding with NMF for face recognition

Jagath C. Rajapakse, Menaka Rajapakse, Jeffrey Tan, 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

Sub-population analysis based on temporal features of high content images

Roy E. Welsch, Jagath C. Rajapakse, James Evans, 2009, BMC Bioinformatics.

A deep neural network approach to predicting clinical outcomes of neuroblastoma patients

Francisco Azuaje, Jagath C. Rajapakse, Léon-Charles Tranchevent, 2019, BMC Medical Genomics.

Determination of the Relative Importance of Gene Function or Taxonomic Grouping to Codon Usage Bias Using Cluster Analysis and SVMs

Jagath C. Rajapakse, Gary B. Fogel, Jianmin Ma, 2006, 2006 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology.

Human Brain Anatomical Connectivity Analysis Using Sequential Sampling and Resampling

Bo Zheng, Jagath C. Rajapakse, 2007, PRIB.

Neuromorphic model for information fusion

Jagath C. Rajapakse, R. Acharya, R. Acharya, 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

Modeling hemodynamic variability with fuzzy features for detecting brain activation from fMR time-series

Juan Zhou, Jagath C. Rajapakse, Juan Zhou, 2007, Neural Computing and Applications.

Adaptive blind signal and image processing: learning algorithms and applications [Book Review]

Jagath C. Rajapakse, 2003, IEEE Transactions on Neural Networks.

Mixed Spectrum Analysis on fMRI Time-Series

Arun Kumar, Feng Lin, Jagath C. Rajapakse, 2016, IEEE Transactions on Medical Imaging.

Neural network modeling of neuronal-vascular coupling

Jagath C. Rajapakse, V. Venkatraman, 1999, ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378).

Toward Better Understanding of Protein Secondary Structure: Extracting Prediction Rules

Jacek M. Zurada, Jagath C. Rajapakse, Minh Ngoc Nguyen, 2011, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Two-Stage support vector machines for protein secondary structure prediction

Jagath C. Rajapakse, Minh Ngoc Nguyen, M. N. Nguyen, 2003, Neural Parallel Sci. Comput..

Combining Semantic Similarity and GO Enrichment for Computation of Functional Similarity

Jianjun Liu, Jagath C. Rajapakse, Wenting Liu, 2017, bioRxiv.

Simultaneous Sample and Gene Selection Using T-score and Approximate Support Vectors

Jagath C. Rajapakse, Piyushkumar A. Mundra, D. A. K. Maduranga, 2013, PRIB.

Cerebral and hippocampal volumetry in early Alzheimer's disease

Jagath C. Rajapakse, Yih-Yian Sitoh, J. Karthik, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

NURBS snakes

Ravinda G. N. Meegama, Jagath C. Rajapakse, R. Meegama, 2003, Image Vis. Comput..

Spatiotemporal Analysis of Functional Images Using the Fixed Effect Model

Jagath C. Rajapakse, Jayasanka Piyaratna, 2001, IPMI.

Gene Classification Using Codon Usage and Support Vector Machines

Jagath C. Rajapakse, Jianmin Ma, Minh Ngoc Nguyen, 2009, IEEE ACM Trans. Comput. Biol. Bioinform..

Support Vector Based T-Score for Gene Ranking

Jagath C. Rajapakse, Piyushkumar A. Mundra, P. Mundra, 2008, PRIB.

Stability of Inferring Gene Regulatory Structure with Dynamic Bayesian Networks

Jagath C. Rajapakse, Iti Chaturvedi, 2011, PRIB.

A deep neural network approach to predicting clinical outcomes of neuroblastoma patients

Jagath C. Rajapakse, Francisco Azuaje, Léon-Charles Tranchevent, 2019, BMC Medical Genomics.

Improving signal-to-noise ratio of structured light microscopy based on photon reassignment

Jagath C. Rajapakse, Peter T. C. So, George Barbastathis, 2011, Biomedical optics express.

Detecting functional modules of the brain using eigen value decomposition of the signless Laplacian

Jagath C. Rajapakse, Shaohua Li, Xiuchao Sui, 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

Fusion of Gene Regulatory and Protein Interaction Networks Using Skip-Chain Models

Jagath C. Rajapakse, Iti Chaturvedi, 2008, PRIB.

Multi-class Protein Subcellular Localization Classification Using Support Vector Machines

Jagath C. Rajapakse, Peng Wai Meng, 2005, CIBCB.

Mixed spectrum analysis in spatial context: Application to fMRI

Arun Kumar, Lin Feng, Jagath C. Rajapakse, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

Robust Algorithm for Finding Weak Motifs

Xiao Yang, Jagath C. Rajapakse, 2005, 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

Time-Frequency Method Based Activation Detection in Functional MRI Time-Series

Arun Kumar, Jagath C. Rajapakse, 2007, PRIB.

Pattern Recognition in Bioinformatics, Second IAPR International Workshop, PRIB 2007, Singapore, October 1-2, 2007, Proceedings

Bertil Schmidt, Jagath C. Rajapakse, Gwenn Volkert, 2007, PRIB.

Protein localization on cellular images with Markov random fields

Song Liu, Jagath C. Rajapakse, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Segmentation of subcortical brain structures using fuzzy templates

Juan Zhou, Jagath C. Rajapakse, Juan Zhou, 2005, NeuroImage.

General Framework for Two-stage Approaches to Protein Secondary Structure Prediction

Jagath C. Rajapakse, Minh N. Aguyen, 2003 .

Guest Editors' Introduction to the Special Section: Computational Intelligence Approaches in Computational Biology and Bioinformatics

Yanqing Zhang, Jagath C. Rajapakse, Gary B. Fogel, 2007, IEEE ACM Trans. Comput. Biol. Bioinform..

Amino Acid Features for Prediction of Protein-Protein Interface Residues with Support Vector Machines

Jagath C. Rajapakse, Minh Ngoc Nguyen, Kaibo Duan, 2007, EvoBIO.

Gene and sample selection using T-score with sample selection

Jagath C. Rajapakse, Piyushkumar A. Mundra, P. Mundra, 2016, J. Biomed. Informatics.

Ovarian cancer classification with missing data

Jagath C. Rajapakse, C. Renz, K. Razvi, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Tree-structured algorithm for long weak motif discovery

Wen-Jing Hsu, Malcolm Yoke-Hean Low, Jagath C. Rajapakse, 2011, Bioinform..

Optimal approach to sequence-to-sequence prediction: applications in bioinformatics

Jagath C. Rajapakse, Minh N. Nguyen, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Fuzzy region integration approach for subcortical structure segmentation

Jagath C. Rajapakse, Shichun Peng, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Analysis of correlation-based biomolecular networks from different omics data by fitting stochastic block models.

Jagath C. Rajapakse, Francisco Azuaje, Katharina Baum, 2019, F1000Research.

Probabilistic Framework for Brain Connectivity From Functional MR Images

Yang Wang, Juan Zhou, Jagath C. Rajapakse, 2008, IEEE Transactions on Medical Imaging.

Stability of building gene regulatory networks with sparse autoregressive models

Jagath C. Rajapakse, Piyushkumar A. Mundra, P. Mundra, 2011, BMC Bioinformatics.

Input encoding method for identifying transcription start sites in RNA polymerase II promoters by neural networks

Jagath C. Rajapakse, Loi Sy Ho, 2006, Soft Comput..

Effect of Diffusion Weighting and Number of Sensitizing Directions on Fiber Tracking in DTI

Bo Zheng, Jagath C. Rajapakse, 2006, ICONIP.

FPGA Implementations of Neural Networks

Jagath C. Rajapakse, Amos R. Omondi, A. Omondi, 2006 .

Learning functional structure from fMR images

Jagath C. Rajapakse, Xuebin Zheng, Xuebin Zheng, 2006, NeuroImage.

Pattern Recognition in Bioinformatics

Jagath C. Rajapakse, Raj Acharya, Lirnsoon Wong, 2014, Lecture Notes in Computer Science.

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

Elena Marchiori, Jason H. Moore, Jagath C. Rajapakse, 2007, Lecture Notes in Computer Science.

Bayesian approach to segmentation of statistical parametric maps

Jagath C. Rajapakse, Jayasanka Piyaratna, Jagath Rajapakse, 2001, IEEE Transactions on Biomedical Engineering.

LVQ Approach Using AA Indices for Protein Subcellular Localisation Prediction

Jagath C. Rajapakse, Minh Ngoc Nguyen, Kok-Sin Toh, 2005, 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

Neural networks in FPGAs

Jagath C. Rajapakse, A. R. Omondi, A. Omondi, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Staging tissues with conditional random fields

Song Liu, Jagath C. Rajapakse, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

ListMotif: A time and memory efficient algorithm for weak motif discovery

Jagath C. Rajapakse, Wen Jing Hsu, Malcolm Yoke Hean Low, 2010, 2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering.

Extraction of Fuzzy Features for Detecting Brain Activation from Functional MR Time-Series

Juan Zhou, Jagath C. Rajapakse, J. Rajapakse, 2006, ICONIP.

Extracting EEG rhythms using ICA-R

Swathi Kavuri Sri, Jagath C. Rajapakse, Jagath Rajapakse, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Ambivert degree identifies crucial brain functional hubs and improves detection of Alzheimer’s Disease and Autism Spectrum Disorder

Roy E. Welsch, Jagath C. Rajapakse, Sukrit Gupta, 2020, NeuroImage: Clinical.

High sensitivity technique for translation initiation site detection

Jagath C. Rajapakse, Loi Sy Ho, 2004, 2004 Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

Machine Learning in Bioinformatics

Jagath C. Rajapakse, Yan-Qing Zhang, Yanqing Zhang, 2008 .

Correlation of cell membrane dynamics and cell motility

Roy E. Welsch, Jagath C. Rajapakse, Paul Matsudaira, 2011, BMC Bioinformatics.

F-score with Pareto Front Analysis for Multiclass Gene Selection

Jagath C. Rajapakse, Piyushkumar A. Mundra, 2009, EvoBIO.

Parameter estimation of fMRI time-series using frequency analysis

Keng Wah Choo, Jagath C. Rajapakse, 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

Named Entity Analysis and Extraction with Uncommon Words pdf

Erik Cambria, Jagath C. Rajapakse, Xiaoshi Zhong, 2018, ArXiv.

Adaptive blind signal and image processing: learning algorithms and applications: A. Cichocki, S. Amari, Wiley, New York, 2002, 586pp., ISBN 0471 60791 6

Jagath C. Rajapakse, Jagath Rajapakse, 2002, Neurocomputing.

Power spectral based detection of brain activation from fMR images

Arun Kumar, Jagath C. Rajapakse, 2007, Neural Computing and Applications.

Predicting Affective States of Programming Using Keyboard Data and Mouse Behaviors

Jagath C. Rajapakse, Owen Noel Newton Fernando, Hualin Liu, 2018, 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV).

Comparative study of implementing ICNNs on FPGAs

Jagath C. Rajapakse, A. R. Omondi, A. B. Lim, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

Ultra-Fast fMRI Imaging with High-Fidelity Activation Map

Juan Zhou, A. G. Ramakrishnan, Manojkumar Saranathan, 2006, ICONIP.

Obtaining leaner deep neural networks for decoding brain functional connectome in a single shot

Jagath C. Rajapakse, Sukrit Gupta, Yi Hao Chan, 2021, Neurocomputing.

ICA Gives Higher-Order Functional Connectivity of Brain

Jagath C. Rajapakse, Kanyan Yang, Jagath Rajapakse, 2004 .

Regional MRI measurements of the corpus callosum: a methodological and developmental study

Jagath C. Rajapakse, Jay N. Giedd, Judith L. Rapoport, 1996, Brain and Development.

GO2Vec: transforming GO terms and proteins to vector representations via graph embeddings

Jagath C. Rajapakse, Xiaoshi Zhong, Rama Kaalia, 2019, BMC Genomics.

Sexual dimorphism of the developing human brain

Jagath C. Rajapakse, Jay N. Giedd, F. Xavier Castellanos, 1997, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

Gene Ontology Enrichment Improves Performances of Functional Similarity of Genes

Jagath C. Rajapakse, Wenting Liu, Jianjun Liu, 2018, Scientific Reports.

Quantitative magnetic resonance imaging of the corpus callosum in childhood onset schizophrenia

Jagath C. Rajapakse, Jay N. Giedd, Judith L. Rapoport, 1997, Psychiatry Research: Neuroimaging.

Quantitative Magnetic Resonance Imaging of Human Brain Development: Ages 4–18

Jagath C. Rajapakse, Jay N. Giedd, B. J. Casey, 1996 .

Development of the human corpus callosum during childhood and adolescence: A longitudinal MRI study

Jagath C. Rajapakse, J. Rajapakse, J. Blumenthal, 1999, Progress in Neuro-Psychopharmacology and Biological Psychiatry.