Professor Madhu Chetty
Professor, Information Technology
Professor Madhu Chetty is internationally recognised for his research in the application of artificial intelligence (AI) and machine learning (ML) to bioinformatics and digital health. Professor Chetty also has expertise in evolutionary optimisation, big data, natural language processing, and block chain. He has prolific publication record with more than 75% of his Q1 publications in Top Ten percentile. Madhu was lead CI in Cat-1 competitive grants, such as the AISRF. He serves as the Director of the AI and ML stream in the University’s Health Innovation and Transformation Centre. He serves on the editorial board of PLOS ONE and Elsevier’s Biosystems journal. As General Chair, he hosted the 18th IEEE CIBCB conference.
He has received the Overall Award for Excellence in Graduate Research Supervision, and also the Vice Chancellor's Certificate of Commendation for Excellence in Community Engagement and Impact. Amity University, India, conferred him with a Citation and Lifetime Professorship.
PANDORA: Deep Graph Learning Based COVID-19 Infection Risk Level Forecasting
A Robust Ensemble Regression Model for Reconstructing Genetic Networks
Knowledge-Based Intelligent Text Simplification for Biological Relation Extraction
Meaning-Sensitive Text Data Augmentation with Intelligent Masking
MICFuzzy: A maximal information content based fuzzy approach for reconstructing genetic networks
User authentication and access control to blockchain-based forensic log data
Adoption of Blockchain Technology: Exploring the Factors Affecting Organizational Decision
Blockchain Based Smart Auction Mechanism for Distributed Peer-to-Peer Energy Trading
Combining kinetic orders for efficient S-System modelling of gene regulatory network
Computational intelligence and machine learning in bioinformatics and computational biology
Ensemble Regression Modelling for Genetic Network Inference
Filter feature selection based Boolean Modelling for Genetic Network Inference
Incorporating Price Information in Blockchain-based Energy Trading
Integrating steady-state and dynamic gene expression data for improving genetic network modelling
Resilience of Stablecoin Reserve for Distributed Energy Trading
2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) : 13-15 Oct. 2021
An efficient boolean modelling approach for genetic network inference
An improved memetic approach for protein structure prediction incorporating maximal hydrophobic core estimation concept
Cost Effective Annotation Framework Using Zero-Shot Text Classification
Dynamically regulated initialization for S-system modelling of genetic networks
Factors affecting the organizational adoption of blockchain technology: An Australian perspective
Blockchain Technology (BCT) is a novel innovation that has the potential to transform industries,...
Factors affecting the organizational adoption of blockchain technology: Extending the technology–organization– environment (TOE) framework in the Australian context
Blockchain technology (BCT) has been gaining popularity due to its benefits for almost every...
From general language understanding to noisy text comprehension
An Exploratory Study of the Adoption of Blockchain Technology Among Australian Organizations: A Theoretical Model
Scholarly and commercial literature indicates several applications of Blockchain Technology (BCT)...
Multimodal Memetic Framework for low-resolution protein structure prediction
In this paper, we propose a systematic design of evolutionary optimization, namely Multimodal...
Pre-trained Language Models with Limited Data for Intent Classification
Intent analysis is capturing the attention of both the industry and academia due to its...
Assessing transformer oil quality using deep convolutional networks
Electrical power grids comprise a significantly large number of transformers that interconnect...
Challenges and opportunities for Blockchain Technology adoption: A systematic review
Blockchain technology promises to significantly impact current business processes in industries...
Reverse engineering genetic networks using nonlinear saturation kinetics
A gene regulatory network (GRN) represents a set of genes along with their regulatory...
Towards Machine Learning approach for Digital-Health intervention program
Digital-Health intervention (DHI) are used by health care providers to promote engagement...
Information technology and organizational learning interplay: A survey
The objective of this paper is to provide a systematic review of the evolutionary trends in the...
Large scale modeling of genetic networks using gene knockout data
Gene regulatory network (GRN) represents a set of genes and their regulatory interactions. The...
Modeling neurocognitive reaction time with Gamma distribution
As a broader effort to build a holistic biopsychosocial health metric, reaction time data...
PCA based population generation for genetic network optimization
A gene regulatory network (GRN) represents a set of genes and its regulatory interactions. The...
Relevance of Frequency of Heart-Rate Peaks as Indicator of 'Biological' Stress Level
The biopsychosocial (BPS) model proposes that health is best understood as a combination of...
Special issue on multi-objective reinforcement learning
Exploiting temporal genetic correlations for enhancing regulatory network optimization
Reconstruction of Large-scale gene regulatory network using s-system model
Coupling of Cellular Processes and Their Coordinated Oscillations under Continuous Light in Cyanothece sp ATCC 51142, a Diazotrophic Unicellular Cyanobacterium
Unicellular diazotrophic cyanobacteria such as Cyanothece sp. ATCC 51142 (henceforth Cyanothece),...
Decoupled modeling of gene regulatory networks using Michaelis-Menten kinetics
Frequency decomposition based gene clustering
Gene regulatory network inference using Michaelis-Menten kinetics
Improving gene regulatory network inference using network topology information
Inferring the gene regulatory network (GRN) structure from data is an important problem in...
Influence of mixotrophic growth on rhythmic oscillations in expression of metabolic pathways in diazotrophic cyanobacterium Cyanothece sp ATCC 51142
This study investigates the influence of mixotrophy on physiology and metabolism by analysis of...
Network decomposition based large-scale reverse engineering of gene regulatory network
A Gene Regulatory Network (GRN) is the functional circuitry of a living organism that exhibits...
Stochastic S-system modeling of gene regulatory network
Microarray gene expression data can provide insights into biological processes at a system-wide...
Towards large scale genetic network modeling
Evaluating influence of microRNA in reconstructing gene regulatory networks
Gene regulatory network (GRN) consists of interactions between transcription factors (TFs) and...
Sib-based survival selection technique for protein structure prediction in 3D-FCC lattice model
Significance of Non-edge Priors in Gene Regulatory Network Reconstruction
It is well known that incorporating prior knowledge improves gene regulatory network...
A knowledge-based initial population generation in memetic algorithm for protein structure prediction
A model of the circadian clock in the cyanobacterium Cyanothece sp ATCC 51142
Background: The over consumption of fossil fuels has led to growing concerns over climate change...
An adaptive strategy for assortative mating in genetic algorithm
A priority based parental selection method for genetic algorithm
Clustered Memetic Algorithm With Local Heuristics for Ab Initio Protein Structure Prediction
Low-resolution protein models are often used within a hierarchical framework for structure...
Diurnal rhythm of a unicellular diazotrophic cyanobacterium under mixotrophic conditions and elevated carbon dioxide
Mixotrophic cultivation of cyanobacteria in wastewaters with flue gas sparging has the potential...
Incorporating time-delays in S-System model for reverse engineering genetic networks
Background: In any gene regulatory network (GRN), the complex interactions occurring amongst...
Inferring large scale genetic networks with S-system model
mDBN: Motif based learning of gene regulatory networks using dynamic Bayesian networks
On the analysis of time-delayed interactions in genetic network using S-system model
Protein structure prediction with a new composite measure of diversity and memory-based diversification strategy
Reverse engineering genetic networks with time-delayed S-system model and pearson correlation coefficient
Rhythmic and sustained oscillations in metabolism and gene expression of Cyanothece sp ATCC 51142 under constant light
Cyanobacteria, a group of photosynthetic prokaryotes, oscillate between day and nighttime...
Adaptive regulatory genes cardinality for reconstructing genetic networks
Data discretization for dynamic Bayesian network based modeling of genetic networks
FusGP: Bayesian co-learning of gene regulatory networks and protein interaction networks
Gene regulatory network modeling via global optimization of high-order dynamic Bayesian network
Background: Dynamic Bayesian network (DBN) is among the mainstream approaches for modeling...
Issues impacting genetic network reverse engineering algorithm validation using small networks
Genetic network reverse engineering has been an area of intensive research within the systems...
Local and global algorithms for learning dynamic Bayesian networks
On the reconstruction of genetic network from partial microarray data
Gene Regulatory Network (GRN) contains interactions occurring between transcription factors (TF)...
Protein structure prediction based on optimal hydrophobic core formation
Simultaneous learning of instantaneous and time-delayed genetic interactions using novel information theoretic scoring technique
Background: Understanding gene interactions is a fundamental question in systems biology....
A Markov-Blanket-Based Model for Gene Regulatory Network Inference
An efficient two-step Markov blanket method for modeling and inferring complex regulatory...
A memetic approach to protein structure prediction in triangular lattices
Protein structure prediction (PSP) remains one of the most challenging open problems in...
An improved method to infer Gene Regulatory Network using S-System
Combining instantaneous and time-delayed interactions between genes - A two phase algorithm based on information theory
Conflict resolution based global search operators for long protein structures prediction
Most population based evolutionary algorithms (EAs) have struggled to accurately predict...
Dynamic Bayesian network modeling of cyanobacterial biological processes via gene clustering
GlobalMIT: learning globally optimal dynamic bayesian network with the mutual information test criterion
Motivation: Dynamic Bayesian networks (DBN) are widely applied in modeling various biological...
Information theoretic dynamic Bayesian network approach for reconstructing genetic networks
Multi agent carbon trading incorporating human traits and game theory
Novel local improvement techniques in clustered memetic algorithm for protein structure prediction
Evolutionary algorithms (EAs) often fail to find the global optimum due to genetic drift. As the...
Polynomial time algorithm for learning globally optimal dynamic bayesian network
Reconstructing genetic networks with concurrent representation of instantaneous and time-delayed interactions
Simultaneous learning of instantaneous and time-delayed genetic interactions using novel information theoretic scoring technique
Understanding gene interactions is a fundamental question in systems biology. Currently, modeling...
Twin Removal in Genetic Algorithms for Protein Structure Prediction Using Low-Resolution Model
This paper presents the impact of twins and the measures for their removal from the population of...
Binary-organoid particle swarm optimisation for inferring genetic networks
A holistic understanding of genetic interactions is crucial in the analysis of complex biological...
Clustered memetic algorithm for protein structure prediction
Memetic algorithm (MA) often perform better than other evolutionary algorithm due to their...
Computational intelligence in bioinformatics
No abstract available]
DFS-generated pathways in GA crossover for protein structure prediction
Genetic algorithms (GAs), as nondeterministic conformational search techniques, are promising for...
Modelling gene regulatory networks using computational intelligence techniques
Multiclass microarray gene expression classification based on fusion of correlation features
In this paper, we propose novel algorithmic models based on fusion of independent and correlated...
Pattern recognition in bioinformatics
[No abstract available]
Combining segmental semi-Markov models with neural networks for protein secondary structure prediction
Degree of differential prioritization
Extended HP model for protein structure prediction
This paper describes a detailed investigation of a lattice-based HP (hydrophobic-hydrophilic)...
Genetic algorithm in ab initio protein structure prediction using low resolution model: a review
Proteins are sequences of amino acids bound into a linear chain that adopt a specific folded...
MCMC based Bayesian inference for modelling gene networks
In this paper, we apply Bayesian networks (BN) to infer gene regulatory network (GRN) model from...
Multiclass microarray gene expression analysis based on mutual dependency models
Novel memetic algorithm for protein structure prediction
A novel Memetic Algorithm (MA) is proposed for investigating the complex ab initio protein...
A study on the importance of differential prioritization in feature selection using toy datasets
Constraint minimization for efficient modelling of gene regulatory network
Due to various complexities, as well as noise and high dimensionality, reconstructing a gene...
DFS based partial pathways in GA for protein structure prediction
Nondeterministic conformational search techniques, such as Genetic Algorithms (GAs) are promising...
Generating synthetic gene regulatory networks
Reconstructing GRN from microarray dataset is a very challenging problem as these datasets...
Hidden Markov models Incorporating fuzzy measures and integrals for protein sequence identification and alignment
A framework for path analysis in gene regulatory networks
The inference of a network structure from microarray data providing dynamical information about...
Characteristics of predictor sets found using differential prioritization
Background: Feature selection plays an undeniably important role in classification problems...
Generalized schemata theorem incorporating twin removal for protein structure prediction
The schemata theorem, on which the working of Genetic Algorithm (GA) is based in its current...
Learning structure of a gene regulatory network
Bayesian segmentation using residue proximity for secondary structure and contact prediction
Secondary structure, residue contacts and contact numbers play an important role in tertiary...
Differential prioritization between relevance and redundancy in correlation-based feature selection techniques for multiclass gene expression data
Background: Due to the large number of genes in a typical microarray dataset, feature selection...
Investigating the class-specific relevance of predictor sets obtained from DDP-based feature selection technique
Feature selection is crucial to tumor classification due to the high dimensionality of microarray...
A comparative study of two novel predictor set scoring methods
Due to the large number of genes measured in a typical microarray dataset, feature selection...
A frequency response based design of suboptimal reduced order controller
A novel approach for designing reduced order suboptimal controllers is presented. It is based on...
An architecture combining Bayesian segmentation and neural network ensembles for protein secondary structure prediction
A combined architecture of Bayesian segmentation along with ensembles of two layered feedforward...
An efficient algorithm for computing the fitness function of a hydrophobic-hydrophilic model
The protein folding problem is a minimization problem in which the energy function is often...
A new guided genetic algorithm for 2D hydrophobic-hydrophilic model to predict protein folding
This paper presents a novel Guided Genetic Algorithm (GGA) for protein folding prediction (PFP)...
An incremental constructive layer neural network based power system stabiliser
In this paper, a systematic approach for a neural network based Power System Stabiliser (PSS)...
Evaluation of fuzzy measures in profile hidden Markov models for protein sequences
In biological problems such as protein sequence family identification and profile building the...
Fuzzy profile Hidden Markov models for protein sequence analysis
Profile HMMs based on classical hidden Markov models have been widely applied for alignment and...
Increasing classification accuracy by combining adaptive sampling and convex pseudo-data
The availability of microarray data has enabled several studies on the application of aggregated...
Partially computed fitness function based genetic algorithm for hydrophobic-hydrophilic model
Fitness computation after each crossover or mutation operation in Genetic Algorithm (GA) requires...
An interactive Java-based educational module in electromagnetics
Fuzzy logic based discrete mode power system stabilizer
Towards a web-based control engineering laboratory
Distance education via the World Wide Web (WWW) in engineering should include laboratory...