World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
6315
World Ranking
10215
National Ranking
310

Research.com Recognitions

  • 2015 - ACM Senior Member

Overview

Abdul Sattar is a researcher affiliated with Griffith University in Australia, producing work primarily situated within the fields of Biochemistry, Genetics and Molecular Biology, and Computer Science. Their multidisciplinary focus combines extensive expertise in molecular biology with computational approaches, reflecting a strong emphasis on both life sciences and information technology.

Their research spans several subfields, including Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, and Industrial and Manufacturing Engineering. Sattar's scholarly output covers a wide range of topics, particularly concentrating on Protein Structure and Dynamics, Machine Learning in Bioinformatics, and Computational Drug Discovery Methods. Additional topics in their work include Water Quality Monitoring Technologies, RNA and protein synthesis mechanisms, Enzyme Structure and Function, and Bioinformatics and Genomic Networks.

Their recent notable papers demonstrate this interdisciplinary breadth:

  • "Neurological Manifestations of COVID-19 (SARS-CoV-2): A Review" (2020), published in Frontiers in Neurology
  • "Synthesis, in vitro bio-evaluation, and molecular docking study of thiosemicarbazone-based isatin/bis-Schiff base hybrid analogues as effective cholinesterase inhibitors" (2023), published in Journal of Molecular Structure
  • "Consumer's intention to purchase 5G: Do environmental awareness, environmental knowledge and health consciousness attitude matter?" (2021), published in Technology in Society
  • "Review of modelling and simulation strategies for evaluating corrosive behavior of aqueous amine systems for CO2 capture" (2020), published in International Journal of Greenhouse Gas Control
  • "CardioTox net: a robust predictor for hERG channel blockade based on deep learning meta-feature ensembles" (2021), published in Journal of Cheminformatics

Frequently publishing in venues such as Scientific Reports, SSRN Electronic Journal, and South Asian Journal of Emergency Medicine, Sattar has contributed to journals relating to both scientific research and technological applications. Other common venues include Internet of Things and IEEE Access.

Their collaborative network includes frequent co-authors such as M. A. Hakim Newton, Jarrod Trevathan, Julia Rahman, Abdul Karim, and Abdollah Dehzangi, indicating sustained partnerships across multiple research projects.

In recognition of professional standing, Abdul Sattar was awarded the ACM Senior Member distinction in 2015, reflecting a formal acknowledgment within the computing community.

Best Publications

  • Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning.

    Rhys Heffernan;Kuldip Paliwal;James Lyons;Abdollah Dehzangi

  • Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou׳s general PseAAC

    Abdollah Dehzangi;Abdollah Dehzangi;Rhys Heffernan;Alok Sharma;Alok Sharma;James Lyons

  • Local search with edge weighting and configuration checking heuristics for minimum vertex cover

    Shaowei Cai;Kaile Su;Abdul Sattar

  • SPIDER2: A Package to Predict Secondary Structure, Accessible Surface Area, and Main-Chain Torsional Angles by Deep Neural Networks

    Yuedong Yang;Rhys Heffernan;Kuldip Paliwal;James Lyons

  • Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network.

    James G. Lyons;Abdollah Dehzangi;Abdollah Dehzangi;Rhys Heffernan;Alok Sharma;Alok Sharma

  • NuMVC: an efficient local search algorithm for minimum vertex cover

    Shaowei Cai;Kaile Su;Chuan Luo;Abdul Sattar

  • AI 2006: Advances in Artificial Intelligence

    Abdul Sattar;Byeong-Ho Kang

  • EASE-MM: Sequence-Based Prediction of Mutation-Induced Stability Changes with Feature-Based Multiple Models

    Lukas Folkman;Lukas Folkman;Bela Stantic;Abdul Sattar;Abdul Sattar;Yaoqi Zhou

  • INDu : An Interval & Duration Network

    Arun K. Pujari;Arun K. Pujari;G. Vijaya Kumari;G. Vijaya Kumari;Abdul Sattar;Abdul Sattar

  • Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins

    Rhys Heffernan;Abdollah Dehzangi;Abdollah Dehzangi;James G. Lyons;Kuldip K. Paliwal

  • INDU: An Interval and Duration Network

    Arun K. Pujari;G. Vijaya Kumari;Abdul Sattar

  • Twin Removal in Genetic Algorithms for Protein Structure Prediction Using Low-Resolution Model

    Tamjidul Hoque;Madhu Chetty;Andrew Lewis;Abdul Sattar

  • PSSM-Suc: Accurately predicting succinylation using position specific scoring matrix into bigram for feature extraction

    Abdollah Dehzangi;Yosvany López;Sunil Pranit Lal;Ghazaleh Taherzadeh

  • PRICAI 2002: Trends in Artificial Intelligence

    Mitsuru Ishizuka;Abdul Sattar

  • Proposing a highly accurate protein structural class predictor using segmentation-based features.

    Abdollah Dehzangi;Abdollah Dehzangi;Kuldip K. Paliwal;James G. Lyons;Alok Sharma;Alok Sharma

  • A Combination of Feature Extraction Methods with an Ensemble of Different Classifiers for Protein Structural Class Prediction Problem

    Abdollah Dehzangi;Kuldip Paliwal;Alok Sharma;Omid Dehzangi

  • Extended HP model for protein structure prediction.

    Tamjidul Hoque;Madhusudan Rajgopal Chetty;Abdul Sattar

  • Protein folding prediction in 3D FCC HP lattice model using genetic algorithm

    M.T. Hoque;M. Chetty;A. Sattar

  • A defeasible logic for modelling policy-based intentions and motivational attitudes

    Guido Governatori;Vineet Padmanabhan;Antonino Rotolo;Abdul Sattar

  • Improving succinylation prediction accuracy by incorporating the secondary structure via helix, strand and coil, and evolutionary information from profile bigrams.

    Abdollah Dehzangi;Yosvany López;Sunil Pranit Lal;Ghazaleh Taherzadeh

  • Efficient Toxicity Prediction via Simple Features Using Shallow Neural Networks and Decision Trees

    Abdul Karim;Avinash Mishra;M. A. Hakim Newton;Abdul Sattar

  • A Defeasible Logic of Policy-Based Intention

    Guido Governatori;Vineet Padmanabhan;Abdul Sattar

Frequent Co-Authors

Abdollah Dehzangi
Abdollah Dehzangi Rutgers, The State University of New Jersey
Alok Sharma
Alok Sharma Griffith University
Guido Governatori
Guido Governatori Central Queensland University
Kuldip K. Paliwal
Kuldip K. Paliwal Griffith University
Mehmet A. Orgun
Mehmet A. Orgun Macquarie University
Conrad Sanderson
Conrad Sanderson Commonwealth Scientific and Industrial Research Organisation
Yaoqi Zhou
Yaoqi Zhou Griffith University
Tatsuhiko Tsunoda
Tatsuhiko Tsunoda University of Tokyo
Michael J. Maher
Michael J. Maher University of New South Wales
Yuedong Yang
Yuedong Yang Sun Yat-sen University

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