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Madhu Chetty
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2020 – today
- 2024
- [j32]Shuo Yu
, Feng Xia
, Yueru Wang, Shihao Li, Falih Gozi Febrinanto
, Madhu Chetty
:
PANDORA: Deep Graph Learning Based COVID-19 Infection Risk Level Forecasting. IEEE Trans. Comput. Soc. Syst. 11(1): 717-730 (2024) - [i1]Shuo Yu, Feng Xia, Yueru Wang, Shihao Li, Falih Febrinanto, Madhu Chetty:
PANDORA: Deep graph learning based COVID-19 infection risk level forecasting. CoRR abs/2406.06618 (2024) - 2023
- [j31]Md. Ezazul Islam
, Md. Rafiqul Islam, Madhu Chetty, Suryani Lim, Mehmood Chadhar:
User authentication and access control to blockchain-based forensic log data. EURASIP J. Inf. Secur. 2023(1): 7 (2023) - [j30]Jaskaran Gill
, Madhu Chetty
, Suryani Lim, Jennifer Hallinan:
Knowledge-Based Intelligent Text Simplification for Biological Relation Extraction. Informatics 10(4): 89 (2023) - [j29]Buddhika Kasthuriarachchy
, Madhu Chetty
, Adrian Shatte
, Darren Walls
:
Meaning-Sensitive Text Data Augmentation with Intelligent Masking. ACM Trans. Intell. Syst. Technol. 14(6): 104:1-104:20 (2023) - [c84]Hasini Nakulugamuwa Gamage, Madhu Chetty, Suryani Lim, Jennifer Hallinan, Huy Nguyen:
A Robust Ensemble Regression Model for Reconstructing Genetic Networks. IJCNN 2023: 1-8 - 2022
- [j28]Jaskaran Gill
, Madhu Chetty, Adrian Shatte, Jennifer Hallinan:
Combining kinetic orders for efficient S-System modelling of gene regulatory network. Biosyst. 220: 104736 (2022) - [j27]Hasini Nakulugamuwa Gamage, Madhu Chetty, Adrian Shatte, Jennifer Hallinan:
Filter feature selection based Boolean Modelling for Genetic Network Inference. Biosyst. 221: 104757 (2022) - [j26]Madhu Chetty, Jennifer Hallinan, Gonzalo A. Ruz
, Anil Wipat:
Computational intelligence and machine learning in bioinformatics and computational biology. Biosyst. 222: 104792 (2022) - [c83]Md. Ezazul Islam, Madhu Chetty, Suryani Lim, Mehmood Chadhar, Syed Islam:
Incorporating Price Information in Blockchain-based Energy Trading. AMCIS 2022 - [c82]Hasini Nakulugamuwa Gamage, Madhu Chetty, Adrian Shatte, Jennifer Hallinan:
Ensemble Regression Modelling for Genetic Network Inference. CIBCB 2022: 1-8 - [c81]Jaskaran Gill, Madhu Chetty, Adrian Shatte, Jennifer Hallinan:
Integrating steady-state and dynamic gene expression data for improving genetic network modelling. CIBCB 2022: 1-8 - [c80]Md. Kamrul Islam, Madhu Chetty, Suryani Lim, Mehmood Chadhar, Syed Islam:
Blockchain Based Smart Auction Mechanism for Distributed Peer-to-Peer Energy Trading. HICSS 2022: 1-10 - 2021
- [j25]Rumana Nazmul, Madhu Chetty
, Ahsan Raja Chowdhury:
An improved memetic approach for protein structure prediction incorporating maximal hydrophobic core estimation concept. Knowl. Based Syst. 219: 104395 (2021) - [c79]Hasini Nakulugamuwa Gamage, Madhu Chetty, Adrian Shatte, Jennifer Hallinan:
An Efficient Boolean Modelling Approach for Genetic Network Inference. CIBCB 2021: 1-8 - [c78]Jaskaran Gill, Madhu Chetty, Adrian Shatte, Jennifer Hallinan:
Dynamically Regulated Initialization for S-system Modelling of Genetic Networks. CIBCB 2021: 1-8 - [c77]Muhammad Saleem Malik, Mehmood Chadhar, Madhu Chetty:
Factors Affecting the Organizational Adoption of Blockchain Technology: An Australian Perspective. HICSS 2021: 1-10 - [c76]Buddhika Kasthuriarachchy
, Madhu Chetty, Adrian Shatte, Darren Walls:
Cost Effective Annotation Framework Using Zero-Shot Text Classification. IJCNN 2021: 1-8 - [e2]Jennifer Hallinan, Madhu Chetty, Gonzalo Ruz Heredia, Adrian Shatte, Suryani Lim:
IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2021, Melbourne, Australia, October 13-15, 2021. IEEE 2021, ISBN 978-1-6654-0112-8 [contents] - 2020
- [j24]Rumana Nazmul, Madhu Chetty
, Ahsan Raja Chowdhury:
Multimodal Memetic Framework for low-resolution protein structure prediction. Swarm Evol. Comput. 52 (2020) - [c75]Saleem Malik, Mehmood A. Chadhar, Madhu Chetty, Savanid Vatanasakdakul:
Adoption of Blockchain Technology among Australian Organizations: A Mixed-Methods Approach. ACIS 2020: 16 - [c74]Saleem Malik, Mehmood Chadhar, Madhu Chetty
, Savanid Vatanasakdakul:
An Exploratory Study of the Adoption of Blockchain Technology Among Australian Organizations: A Theoretical Model. EMCIS 2020: 205-220 - [c73]Buddhika Kasthuriarachchy
, Madhu Chetty
, Gour C. Karmakar, Darren Walls:
Pre-trained Language Models with Limited Data for Intent Classification. IJCNN 2020: 1-9
2010 – 2019
- 2019
- [j23]Meena Santhanagopalan, Madhu Chetty, Cameron Foale, Britt Klein:
Towards Machine Learning approach for Digital-Health intervention program. Aust. J. Intell. Inf. Process. Syst. 15(3): 16-24 (2019) - [j22]Ahammed Sherief Kizhakkethil Youseph, Madhu Chetty
, Gour C. Karmakar:
Reverse engineering genetic networks using nonlinear saturation kinetics. Biosyst. 182: 30-41 (2019) - [c72]Shipra Chhina, Mehmood Chadhar, Savanid Vatanasakdakul, Madhu Chetty:
Challenges and opportunities for Blockchain Technology adoption: A systematic review. ACIS 2019: 81 - 2018
- [c71]Saleem Malik, Madhu Chetty, Mehmood Chadhar:
Information Technology and Organizational Learning Interplay: A Survey. ACIS 2018: 64 - [c70]Meena Santhanagopalan, Madhu Chetty
, Cameron Foale
, Sunil Aryal
, Britt Klein
:
Modeling neurocognitive reaction time with gamma distribution. ACSW 2018: 28:1-28:10 - [c69]Ahammed Sherief Kizhakkethil Youseph
, Madhu Chetty
, Gour C. Karmakar:
Large scale modeling of genetic networks using gene knockout data. ACSW 2018: 34:1-34:8 - [c68]Meena Santhanagopalan, Madhu Chetty
, Cameron Foale
, Sunil Aryal
, Britt Klein
:
Relevance of Frequency of Heart-Rate Peaks as Indicator of 'Biological' Stress Level. ICONIP (7) 2018: 598-609 - 2017
- [j21]Madalina M. Drugan
, Marco A. Wiering
, Peter Vamplew
, Madhu Chetty
:
Special issue on multi-objective reinforcement learning. Neurocomputing 263: 1-2 (2017) - 2016
- [c67]Ahammed Sherief Kizhakkethil Youseph
, Madhu Chetty
, Gour C. Karmakar:
Exploiting Temporal Genetic Correlations for Enhancing Regulatory Network Optimization. ICONIP (1) 2016: 479-487 - 2015
- [j20]Ahsan Raja Chowdhury, Madhu Chetty
:
Network decomposition based large-scale reverse engineering of gene regulatory network. Neurocomputing 160: 213-227 (2015) - [c66]Ahammed Sherief Kizhakkethil Youseph
, Madhu Chetty
, Gour C. Karmakar:
Gene regulatory network inference using Michaelis-Menten kinetics. CEC 2015: 2392-2397 - [c65]Rubaiya Rahtin Khan, Madhu Chetty
:
Towards large scale genetic network modeling. CIBCB 2015: 1-8 - [c64]Md. Abdur Rahman
, Madhu Chetty
, Dieter Bulach
, Pramod P. Wangikar:
Frequency Decomposition Based Gene Clustering. ICONIP (2) 2015: 170-181 - [c63]Ahammed Sherief Kizhakkethil Youseph
, Madhu Chetty
, Gour C. Karmakar:
Decoupled Modeling of Gene Regulatory Networks Using Michaelis-Menten Kinetics. ICONIP (3) 2015: 497-505 - 2014
- [c62]Ajay Nair, Madhu Chetty, Pramod P. Wangikar:
Significance of Non-edge Priors in Gene Regulatory Network Reconstruction. ICONIP (1) 2014: 446-453 - [c61]Rumana Nazmul, Madhu Chetty:
Sib-Based Survival Selection Technique for Protein Structure Prediction in 3D-FCC Lattice Model. ICONIP (2) 2014: 470-478 - 2013
- [j19]Ahsan Raja Chowdhury, Madhu Chetty
, Xuan Vinh Nguyen
:
Incorporating time-delays in S-System model for reverse engineering genetic networks. BMC Bioinform. 14: 196 (2013) - [j18]Xuan Vinh Nguyen, Madhu Chetty
, Ross L. Coppel
, Sandeep Gaudana, Pramod P. Wangikar:
A model of the circadian clock in the cyanobacterium Cyanothece sp. ATCC 51142. BMC Bioinform. 14(S-2): S14 (2013) - [j17]Md. Kamrul Islam, Madhu Chetty
:
Clustered Memetic Algorithm With Local Heuristics for Ab Initio Protein Structure Prediction. IEEE Trans. Evol. Comput. 17(4): 558-576 (2013) - [c60]Rumana Nazmul, Madhu Chetty
:
An Adaptive Strategy for Assortative Mating in Genetic Algorithm. IEEE Congress on Evolutionary Computation 2013: 2237-2244 - [c59]Rumana Nazmul, Madhu Chetty
:
A priority based parental selection method for genetic algorithm. GECCO (Companion) 2013: 125-126 - [c58]Ahsan Raja Chowdhury, Madhu Chetty
, Xuan Vinh Nguyen
:
Inferring large scale genetic networks with S-system model. GECCO 2013: 271-278 - [c57]Nizamul Morshed, Madhu Chetty
, Xuan Vinh Nguyen, Terry Caelli
:
mDBN: motif based learning of gene regulatory networks using dynamic bayesian networks. GECCO 2013: 279-286 - [c56]Rumana Nazmul, Madhu Chetty
:
A Knowledge-Based Initial Population Generation in Memetic Algorithm for Protein Structure Prediction. ICONIP (2) 2013: 546-553 - [c55]Ahsan Raja Chowdhury, Madhu Chetty
, Xuan Vinh Nguyen
:
On the Analysis of Time-Delayed Interactions in Genetic Network Using S-System Model. ICONIP (2) 2013: 616-623 - [c54]Ahsan Raja Chowdhury, Madhu Chetty
, Xuan Vinh Nguyen:
Reverse Engineering Genetic Networks with Time-Delayed S-System Model and Pearson Correlation Coefficient. ICONIP (2) 2013: 624-631 - [c53]Rumana Nazmul, Madhu Chetty
:
Protein Structure Prediction with a New Composite Measure of Diversity and Memory-Based Diversification Strategy. ICONIP (2) 2013: 649-656 - 2012
- [j16]Xuan Vinh Nguyen, Madhu Chetty
, Ross L. Coppel
, Pramod P. Wangikar:
Gene regulatory network modeling via global optimization of high-order dynamic Bayesian network. BMC Bioinform. 13: 131 (2012) - [j15]Nizamul Morshed, Madhu Chetty
, Xuan Vinh Nguyen
:
Simultaneous learning of instantaneous and time-delayed genetic interactions using novel information theoretic scoring technique. BMC Syst. Biol. 6: 62 (2012) - [c52]Ahsan Raja Chowdhury, Madhu Chetty
, Xuan Vinh Nguyen
:
Adaptive regulatory genes cardinality for reconstructing genetic networks. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c51]Rumana Nazmul, Madhu Chetty
, Ram Samudrala, David K. Chalmers
:
Protein structure prediction based on optimal hydrophobic core formation. IEEE Congress on Evolutionary Computation 2012: 1-9 - [c50]Xuan Vinh Nguyen
, Madhu Chetty
, Ross L. Coppel
, Pramod P. Wangikar:
Local and Global Algorithms for Learning Dynamic Bayesian Networks. ICDM 2012: 685-694 - [c49]Xuan Vinh Nguyen
, Madhu Chetty
, Ross L. Coppel
, Pramod P. Wangikar:
Data Discretization for Dynamic Bayesian Network Based Modeling of Genetic Networks. ICONIP (2) 2012: 298-306 - [c48]Nizamul Morshed, Madhu Chetty
, Xuan Vinh Nguyen
:
FusGP: Bayesian Co-learning of Gene Regulatory Networks and Protein Interaction Networks. ICONIP (5) 2012: 369-377 - [c47]Ahsan Raja Chowdhury, Madhu Chetty
, Xuan Vinh Nguyen
:
On the Reconstruction of Genetic Network from Partial Microarray Data. ICONIP (1) 2012: 689-696 - 2011
- [j14]Xuan Vinh Nguyen, Madhu Chetty
, Ross L. Coppel
, Pramod P. Wangikar:
GlobalMIT: learning globally optimal dynamic bayesian network with the mutual information test criterion. Bioinform. 27(19): 2765-2766 (2011) - [j13]Tamjidul Hoque, Madhu Chetty
, Andrew Lewis, Abdul Sattar
:
Twin Removal in Genetic Algorithms for Protein Structure Prediction Using Low-Resolution Model. IEEE ACM Trans. Comput. Biol. Bioinform. 8(1): 234-245 (2011) - [j12]Ramesh Ram, Madhu Chetty
:
A Markov-Blanket-Based Model for Gene Regulatory Network Inference. IEEE ACM Trans. Comput. Biol. Bioinform. 8(2): 353-367 (2011) - [c46]Nizamul Morshed, Madhu Chetty
:
Combining Instantaneous and Time-Delayed Interactions between Genes - A Two Phase Algorithm Based on Information Theory. Australasian Conference on Artificial Intelligence 2011: 102-111 - [c45]Md. Kamrul Islam, Madhu Chetty
, M. Manzur Murshed
:
Novel local improvement techniques in clustered memetic algorithm for protein structure prediction. IEEE Congress on Evolutionary Computation 2011: 1003-1011 - [c44]Ahsan Raja Chowdhury, Madhu Chetty
:
An improved method to infer Gene Regulatory Network using S-System. IEEE Congress on Evolutionary Computation 2011: 1012-1019 - [c43]Nizamul Morshed, Madhu Chetty
:
Reconstructing genetic networks with concurrent representation of instantaneous and time-delayed interactions. IEEE Congress on Evolutionary Computation 2011: 1840-1847 - [c42]Long Tang, Madhu Chetty
, Suryani Lim
:
Multi Agent Carbon Trading Incorporating Human Traits and Game Theory. ICONIP (3) 2011: 36-46 - [c41]Xuan Vinh Nguyen
, Madhu Chetty
, Ross L. Coppel
, Pramod P. Wangikar:
Dynamic Bayesian Network Modeling of Cyanobacterial Biological Processes via Gene Clustering. ICONIP (1) 2011: 97-106 - [c40]Nizamul Morshed, Madhu Chetty
, Xuan Vinh Nguyen
:
Simultaneous Learning of Instantaneous and Time-Delayed Genetic Interactions Using Novel Information Theoretic Scoring Technique. ICONIP (2) 2011: 248-257 - [c39]Md. Kamrul Islam, Madhu Chetty
, Abu Zafer M. Dayem Ullah, Kathleen Steinhöfel
:
A Memetic Approach to Protein Structure Prediction in Triangular Lattices. ICONIP (1) 2011: 625-635 - [c38]Md. Kamrul Islam, Madhu Chetty
, M. Manzur Murshed
:
Conflict Resolution Based Global Search Operators for Long Protein Structures Prediction. ICONIP (1) 2011: 636-645 - [c37]Xuan Vinh Nguyen
, Madhu Chetty
, Ross L. Coppel
, Pramod P. Wangikar:
Polynomial Time Algorithm for Learning Globally Optimal Dynamic Bayesian Network. ICONIP (3) 2011: 719-729 - 2010
- [j11]Madhu Chetty
, Alioune Ngom, Elena Marchiori:
Computational Intelligence in Bioinformatics. Neurocomputing 73(13-15): 2291-2292 (2010) - [j10]Tamjidul Hoque, Madhu Chetty
, Andrew Lewis
, Abdul Sattar
, Vicky M. Avery
:
DFS-generated pathways in GA crossover for protein structure prediction. Neurocomputing 73(13-15): 2308-2316 (2010) - [j9]Shandar Ahmad
, Madhu Chetty
, Bertil Schmidt:
Pattern Recognition in Bioinformatics. Pattern Recognit. Lett. 31(14): 2071-2072 (2010) - [c36]Santi S. Chanthaphavong, Madhu Chetty
:
Binary-Organoid Particle Swarm optimisation for inferring genetic networks. IEEE Congress on Evolutionary Computation 2010: 1-10 - [c35]Md. Kamrul Islam, Madhu Chetty
:
Clustered memetic algorithm for protein structure prediction. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c34]Girija Chetty, Madhu Chetty:
Multiclass microarray gene expression classification based on fusion of correlation features. FUSION 2010: 1-6
2000 – 2009
- 2009
- [j8]Niranjan P. Bidargaddi, Madhu Chetty
, Joarder Kamruzzaman
:
Combining segmental semi-Markov models with neural networks for protein secondary structure prediction. Neurocomputing 72(16-18): 3943-3950 (2009) - [j7]Tamjidul Hoque, Madhu Chetty
, Abdul Sattar
:
Extended HP Model for Protein Structure Prediction. J. Comput. Biol. 16(1): 85-103 (2009) - [c33]Md. Kamrul Islam, Madhu Chetty
:
Novel Memetic Algorithm for Protein Structure Prediction. Australasian Conference on Artificial Intelligence 2009: 412-421 - [c32]Girija Chetty
, Madhu Chetty
:
Multiclass Microarray Gene Expression Analysis Based on Mutual Dependency Models. PRIB 2009: 46-55 - [c31]Ramesh Ram, Madhu Chetty
:
MCMC Based Bayesian Inference for Modeling Gene Networks. PRIB 2009: 293-306 - [p3]Tamjidul Hoque, Madhu Chetty
, Abdul Sattar
:
Genetic Algorithm inAb Initio Protein Structure Prediction Using Low Resolution Model: A Review. Biomedical Data and Applications 2009: 317-342 - 2008
- [j6]Niranjan P. Bidargaddi, Madhu Chetty
, Joarder Kamruzzaman
:
Hidden Markov Models Incorporating Fuzzy Measures and Integrals for Protein Sequence Identification and Alignment. Genom. Proteom. Bioinform. 6(2): 98-110 (2008) - [c30]Tamjidul Hoque, Madhu Chetty, Andrew Lewis
, Abdul Sattar:
DFS Based Partial Pathways in GA for Protein Structure Prediction. PRIB 2008: 41-53 - [c29]Ramesh Ram, Madhu Chetty, Dieter Bulach:
Constraint Minimization for Efficient Modeling of Gene Regulatory Network. PRIB 2008: 201-213 - [c28]Ramesh Ram, Madhu Chetty:
Generating Synthetic Gene Regulatory Networks. PRIB 2008: 237-249 - [c27]Chia Huey Ooi, Shyh Wei Teng, Madhu Chetty:
A Study on the Importance of Differential Prioritization in Feature Selection Using Toy Datasets. PRIB 2008: 311-322 - [e1]Madhu Chetty, Alioune Ngom, Shandar Ahmad
:
Pattern Recognition in Bioinformatics, Third IAPR International Conference, PRIB 2008, Melbourne, Australia, October 15-17, 2008. Proceedings. Lecture Notes in Computer Science 5265, Springer 2008, ISBN 978-3-540-88434-7 [contents] - 2007
- [j5]Chia Huey Ooi, Madhu Chetty
, Shyh Wei Teng
:
Characteristics of predictor sets found using differential prioritization. Algorithms Mol. Biol. 2 (2007) - [j4]Chia Huey Ooi
, Madhu Chetty
, Shyh Wei Teng
:
Differential prioritization in feature selection and classifier aggregation for multiclass microarray datasets. Data Min. Knowl. Discov. 14(3): 329-366 (2007) - [c26]Ramesh Ram, Madhu Chetty
:
Learning Structure of a Gene Regulatory Network. ACIS-ICIS 2007: 525-531 - [c25]Ramesh Ram, Madhu Chetty
:
A guided genetic algorithm for learning gene regulatory networks. IEEE Congress on Evolutionary Computation 2007: 3862-3869 - [c24]Tamjidul Hoque, Madhu Chetty
, Abdul Sattar
:
Protein folding prediction in 3D FCC HP lattice model using genetic algorithm. IEEE Congress on Evolutionary Computation 2007: 4138-4145 - [c23]Tamjidul Hoque, Madhu Chetty, Laurence S. Dooley:
Generalized Schemata Theorem Incorporating Twin Removal for Protein Structure Prediction. PRIB 2007: 84-97 - [c22]Ramesh Ram, Madhu Chetty:
A Framework for Path Analysis in Gene Regulatory Networks. PRIB 2007: 264-273 - 2006
- [j3]Chia Huey Ooi, Madhu Chetty
, Shyh Wei Teng
:
Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass gene expression data. BMC Bioinform. 7: 320 (2006) - [j2]Niranjan P. Bidargaddi, Madhu Chetty, Joarder Kamruzzaman:
Fuzzy measures and integrals in profile hidden Markov models for protein sequence analysis. J. Intell. Fuzzy Syst. 17(6): 541-556 (2006) - [c21]Tamjidul Hoque, Madhu Chetty, Laurence S. Dooley:
A Hybrid Genetic Algorithm for 2D FCC Hydrophobic-Hydrophilic Lattice Model to Predict Protein Folding. Australian Conference on Artificial Intelligence 2006: 867-876 - [c20]Ramesh Ram, Madhu Chetty, Trevor I. Dix:
Fuzzy Model for Gene Regulatory Network. IEEE Congress on Evolutionary Computation 2006: 1450-1455 - [c19]Tamjidul Hoque, Madhu Chetty, Laurence S. Dooley:
A Guided Genetic Algorithm for Protein Folding Prediction Using 3D Hydrophobic-Hydrophilic Model. IEEE Congress on Evolutionary Computation 2006: 2339-2346 - [c18]Niranjan P. Bidargaddi, Madhu Chetty
, Joarder Kamruzzaman
:
Bayesian Segmentation using Residue Proximity for Secondary Structure and Contact Prediction. CIBCB 2006: 1-8 - [c17]Tamjidul Hoque, Madhu Chetty
, Laurence S. Dooley:
Non-Isomorphic Coding in Lattice Model and its Impact for Protein Folding Prediction Using Genetic Algorithm. CIBCB 2006: 1-8 - [c16]Ramesh Ram, Madhu Chetty
, Trevor I. Dix:
Causal Modeling of Gene Regulatory Network. CIBCB 2006: 1-8 - [c15]Chia Huey Ooi
, Madhu Chetty
, Shyh Wei Teng
:
OVA Scheme vs. Single Machine Approach in Feature Selection for Microarray Datasets. ICDM 2006: 10-23 - [c14]Chia Huey Ooi
, Madhu Chetty, Shyh Wei Teng:
Investigating the Class-Specific Relevance of Predictor Sets Obtained from DDP-Based Feature Selection Technique. PRIB 2006: 60-70 - 2005
- [c13]Tamjidul Hoque, Madhu Chetty, Laurence Dooley:
A new guided genetic algorithm for 2D hydrophobic-hydrophilic model to predict protein folding. Congress on Evolutionary Computation 2005: 259-266 - [c12]Niranjan P. Bidargaddi, Madhu Chetty, Joarder Kamruzzaman:
Fuzzy Profile Hidden Markov Models for Protein Sequence Analysis. CIBCB 2005: 427-434 - [c11]Niranjan P. Bidargaddi, Madhu Chetty, Joarder Kamruzzaman:
An Architecture Combining Bayesian segmentation and Neural Network Ensembles for Protein Secondary Structure Prediction. CIBCB 2005: 498-505 - [c10]Niranjan P. Bidargaddi, Madhu Chetty, Joarder Kamruzzaman:
A Fuzzy Viterbi Algorithm for Improved Sequence Alignment and Searching of Proteins. EvoWorkshops 2005: 11-21 - [c9]Chia Huey Ooi
, Madhu Chetty:
A Comparative Study of Two Novel Predictor Set Scoring Methods. IDEAL 2005: 432-439 - [c8]Tamjidul Hoque, Madhu Chetty
, Laurence Dooley:
Efficient Computation of Fitness Function by Pruning in Hydrophobic-Hydrophilic Model. ISBMDA 2005: 346-354 - [c7]Niranjan P. Bidargaddi, Madhu Chetty
, Joarder Kamruzzaman
:
Evaluation of Fuzzy Measures in Profile Hidden Markov Models for Protein Sequences. ISBMDA 2005: 355-366 - [c6]Chia Huey Ooi
, Madhu Chetty
, Shyh Wei Teng
:
Relevance, Redundancy and Differential Prioritization in Feature Selection for Multiclass Gene Expression Data. ISBMDA 2005: 367-378 - [c5]Chia Huey Ooi
, Madhu Chetty:
Increasing Classification Accuracy by Combining Adaptive Sampling and Convex Pseudo-Data. PAKDD 2005: 578-587 - [p2]Niranjan P. Bidargaddi, Madhu Chetty, Joarder Kamruzzaman:
Fuzzy decoding in Profile Hidden Markov Models for protein family identification. Advances in Bioinformatics and Its Applications 2005 - [p1]Chia Huey Ooi
, Madhu Chetty, Iqbal Gondal:
The Role of Feature Redundancy in tumor Classification. Advances in Bioinformatics and Its Applications 2005 - 2004
- [c4]Tamjidul Hoque, Madhu Chetty, Laurence Dooley:
An Efficient Algorithm for Computing the Fitness Function of a Hydrophobic-Hydrophilic Model. HIS 2004: 285-290 - [c3]Tamjidul Hoque, Madhu Chetty, Laurence Dooley:
Partially Computed Fitness Function Based Genetic Algorithm for Hydrophobic-Hydrophilic Model. HIS 2004: 291-296 - 2003
- [c2]Niranjan P. Bidargaddi, Madhu Chetty:
An Incremental Constructive Layer Algorithm for Controller Design. HIS 2003: 58-65 - 2002
- [j1]Madhu Chetty
, Rajkumar Buyya:
Weaving computational grids: how analogous are they with electrical grids? Comput. Sci. Eng. 4(4): 61-71 (2002) - [c1]Madhu Chetty:
Towards a Hybrid Symbolic/Numeric Computational Approach in Controller Design. AISC 2002: 12-25
Coauthor Index
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