Madhu Chetty - Google Scholar Citations

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	All	Since 2015
Citations	1553	613
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Co-authors

Vinh NguyenDeep Learning Solutions Architect at NVIDIA & Machine Learning Scientist, University of MelbourneVerified email at unimelb.edu.au
Md Tamjidul HoqueAssociate Professor of Computer Science, University of New OrleansVerified email at uno.edu
Pramod P WangikarDepartment of Chemical Engineering, Indian Institute of Technology BombayVerified email at iitb.ac.in
Ahsan Raja ChowdhurySenior Consultant, IBM Australia - Casual Academic, School of Eng. and IT, Federation UniversityVerified email at federation.edu.au
Chia-Huey OoiBioinformatics Scientist, Roche Pharma Research and Early Development (pRED)Verified email at roche.com
Ross CoppelMonash University, Faculty of Medicine Nursing and Health ScienceVerified email at monash.edu
Shyh Wei TengFederation University Australia - - School of Science, Engineering and ITVerified email at federation.edu.au
Abdul SattarProfessor of Computer Science, Griffith UniversityVerified email at griffith.edu.au
Andrew LewisAdjunct Associate Professor, School of ICT, Griffith UniversityVerified email at griffith.edu.au
Sandeep Bhupendra GaudanaReliance Industries LimitedVerified email at ril.com
Rajkumar BuyyaCLOUDS Lab, School of Computing and Information Systems, The University of Melbourne, AustraliaVerified email at unimelb.edu.au
Gour KarmakarSenior Lecturer, Federation University, AustraliaVerified email at federation.edu.au
AHAMMED SHERIEF KIZHAKKETHIL...National Institute of Technology CalicutVerified email at nitc.ac.in
Ajay NairColumbia UniversityVerified email at iitb.ac.in
Ganesh A ViswanathanIndian Institute of Technology BombayVerified email at iitb.ac.in
Dieter BulachSenior Research Scientist, VLSCI & EMBL Australia Bioinformatics ResourceVerified email at unimelb.edu.au

Madhu Chetty

Federation University Australia

Verified email at federation.edu.au - Homepage

Computational intelligence evolutionary optimisation machine learning big data analytics bioinformatics


Title	Cited by	Year
Weaving computational grids: how analogous are they with electrical grids? M Chetty, R Buyya Computing in Science & Engineering 4 (4), 61-71, 2002	213	2002
Twin removal in genetic algorithms for protein structure prediction using low-resolution model MT Hoque, M Chetty, A Lewis, A Sattar IEEE/ACM Transactions on Computational Biology and Bioinformatics 8 (1), 234-245, 2009	76	2009
GlobalMIT: learning globally optimal dynamic bayesian network with the mutual information test criterion NX Vinh, M Chetty, R Coppel, PP Wangikar Bioinformatics 27 (19), 2765-2766, 2011	68	2011
Gene regulatory network modeling via global optimization of high-order dynamic bayesian network NX Vinh, M Chetty, R Coppel, PP Wangikar BMC bioinformatics 13 (1), 131, 2012	60	2012
Protein folding prediction in 3D FCC HP lattice model using genetic algorithm MT Hoque, M Chetty, A Sattar 2007 IEEE Congress on Evolutionary Computation, 4138-4145, 2007	56	2007
Extended HP model for protein structure prediction T Hoque, M Chetty, A Sattar Journal of Computational Biology 16 (1), 85-103, 2009	54	2009
Clustered memetic algorithm with local heuristics for ab initio protein structure prediction MK Islam, M Chetty IEEE Transactions on Evolutionary Computation 17 (4), 558-576, 2012	43	2012
Incorporating time-delays in S-System model for reverse engineering genetic networks AR Chowdhury, M Chetty, NX Vinh BMC bioinformatics 14 (1), 196, 2013	42	2013
A new guided genetic algorithm for 2D hydrophobic-hydrophilic model to predict protein folding MT Hoque, M Chetty, LS Dooley 2005 IEEE Congress on Evolutionary Computation 1, 259-266, 2005	37	2005
Genetic Algorithm inAb Initio Protein Structure Prediction Using Low Resolution Model: A Review MT Hoque, M Chetty, A Sattar Biomedical data and applications, 317-342, 2009	36	2009
A hybrid genetic algorithm for 2D FCC hydrophobic-hydrophilic lattice model to predict protein folding MT Hoque, M Chetty, LS Dooley Australasian Joint Conference on Artificial Intelligence, 867-876, 2006	36	2006
Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass gene expression data CH Ooi, M Chetty, SW Teng BMC bioinformatics 7 (1), 320, 2006	36	2006
A guided genetic algorithm for protein folding prediction using 3D hydrophobic-hydrophilic model MT Hoque, M Chetty, LS Dooley 2006 IEEE International Conference on Evolutionary Computation, 2339-2346, 2006	34	2006
Fuzzy model for gene regulatory network R Ram, M Chetty, TI Dix 2006 IEEE International Conference on Evolutionary Computation, 1450-1455, 2006	32	2006
Novel memetic algorithm for protein structure prediction MK Islam, M Chetty Australasian Joint Conference on Artificial Intelligence, 412-421, 2009	31	2009
An improved method to infer gene regulatory network using s-system AR Chowdhury, M Chetty 2011 IEEE Congress of Evolutionary Computation (CEC), 1012-1019, 2011	28	2011
Differential prioritization in feature selection and classifier aggregation for multiclass microarray datasets CH Ooi, M Chetty, SW Teng Data Mining and Knowledge Discovery 14 (3), 329-366, 2007	27	2007
Hybrid Evolutionary Algorithms A Abraham, C Grosan, H Ishibuchi Springer-Verlag Berlin Heidelberg, 2007	26	2007
Causal modeling of gene regulatory network R Ram, M Chetty, TI Dix 2006 IEEE Symposium on Computational Intelligence and Bioinformatics and …, 2006	26	2006
A markov-blanket-based model for gene regulatory network inference R Ram, M Chetty IEEE/ACM transactions on computational biology and bioinformatics 8 (2), 353-367, 2009	25	2009

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