Dr. Ronesh Sharma

Dr. Ronesh Sharma

Position: Assistant Professor
School: School of Electrical & Electronics Engineering
Email: ronesh.sharma@fnu.ac.fj
Campus: Derrick Campus – Samabula
Phone: 3381044 ext.1008
Mobile: 9264802

Biography:
Dr. Ronesh Sharma is an Assistant Professor at the School of Electrical and Electronics Engineering and currently serves as the Associate Dean Research & Innovation at the College of Engineering and Technical Vocational Education and Training (CETVET) at Fiji National University.

Dr. Sharma has made significant contributions to the fields of Electrical and Electronics Engineering, Bioinformatics, and Artificial Intelligence. Additionally, he is experienced in Technical and Vocational Education and Training (TVET) and higher education programmes, with expertise in curriculum development, national and international accreditation, and fostering a high-performance research culture

Qualification:

  • Doctor of Philosophy in Engineering, University of the South Pacific (USP) – Laucala Campus, Suva, Fiji.
  • Master of Engineering in Electronics, Mokpo National University (MNU), Mokpo, South Korea.
  • Bachelor of Engineering Technology (Electrical & Electronics Engineering), University of the South Pacific (USP) – Laucala Campus, Suva, Fiji.

Area of Expertise:

  • Artificial Intelligence
  • Machine Learning
  • Bioinformatics
  • Data Mining
  • Pattern Recognition
  • Robotics and Process Control Engineering Applications
  • Protein Structural Class Prediction Problems
  • Prediction of Disease-Associated Functional Regions
  • Protein Disorder Prediction
  • DNA and RNA Binding Protein Prediction
  • Power Converter Design

Journals:

  • Divnesh Prasad, Ronesh Sharma, M.G.M. Khan, Alok Sharma, “ProtCB-Bind: Protein-carbohydrate binding site prediction using an ensemble of classifiers”, Carbohydrate Research, (2025). Rank: Q2
  • A. Del Conte et al. (2023). “CAID prediction portal: a comprehensive service for predicting intrinsic disorder and binding regions in proteins.” Nucleic Acids Research, gkad430. {R Sharma and A Sharma}. Impact Factor: 19.16. Rank: Q1
  • Sharma, R., et al. (2023). “DRPBind: prediction of DNA, RNA and protein binding residues in intrinsically disordered protein sequences.” bioRxiv: 2023.2003.2020.533427.
  • F. Manavi, A. Sharma, R. Sharma, T. Tsunoda, S. Shatabda, I. Dehzangi, “CNN-Pred: Prediction of Single-Stranded and Double-Stranded DNA-Binding Protein Using Convolutional Neural Networks”, Gene, 2022. Rank: Q2
  • Necci, M., Piovesan, D., CAID Predictors et al. “Critical assessment of protein intrinsic disorder prediction.” Nature Methods, 2021. Link. {R Sharma and A Sharma}. Impact Factor: 48. Rank: Q1
  • S. Kumar, R. Sharma, A. Sharma, “OPTICAL+: a frequency-based deep learning scheme for recognizing brain wave signals”, PeerJ, 2021. Rank: Q1
  • S. Kumar, R. Sharma, T. Tsunoda, T. Kumarevel, A. Sharma, “Forecasting the spread of COVID-19 using LSTM network”, BMC Bioinformatics, 2021. Rank: Q1
  • Viral Dream Consortium, “Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data”, Life Science Alliance, 3:11, 2020. (Team: Ronesh Sharma, Edwin Vans, Ashwini Patil, and Alok Sharma). Impact Factor: 5.781. Rank: Q1
  • R. Sharma, S. Kumar, T. Tsunoda, T. Kumarevel, and A. Sharma, “Single-stranded and double-stranded DNA-binding protein prediction using HMM profiles”, Analytical Biochemistry, vol. 612, 113954, 2020. Impact Factor: 2.219. Rank: Q2
  • R. Sharma, A. Sharma, A. Patil, and T. Tsunoda, “Discovering MoRFs by trisecting intrinsically disordered protein sequence into terminals and middle regions”, BMC Bioinformatics, 2019. Impact Factor: 2.213. Rank: Q1
  • A. Sharma, A. Lysenko, Y. Lopez, A. Dehzangi, R. Sharma, H. Reddy, A. Sattar, and T. Tsunoda, “HseSUMO: Sumoylation site prediction using half-sphere exposures of amino acid residues”, BMC Genomics, 2019. Impact Factor: 3.730. Rank: Q1
  • Viral Dream Consortium, “A crowdsource analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection”, Nature Communications, 2018. Impact Factor: 11.880. Rank: Q1
  • R. Sharma, A. Sharma, T. Tsunoda, and A. Patil, “OPAL+: Improved MoRF prediction in intrinsically disordered protein sequences”, Proteomics, 2018. DOI. Impact Factor: 4.041. Rank: Q1
  • R. Sharma, G. Raicar, T. Tsunoda, A. Patil, and A. Sharma, “OPAL: Prediction of MoRF regions in Intrinsically disordered protein sequence”, Bioinformatics, 2018. Impact Factor: 4.531. Rank: Q1
  • R. Sharma, M. Bayarjargal, T. Tsunoda, A. Patil, and A. Sharma, “MoRFPred-plus: Computational Identification of MoRFs in Protein Sequence using physicochemical properties and HMM profiles”, Journal of Theoretical Biology, 2018. Impact Factor: 2.049. Rank: Q1
  • R. Sharma, S. Kumar, T. Tsunoda, A. Patil, and A. Sharma, “Predicting MoRFS in Protein Sequence using HMM Profiles”, BMC Bioinformatics, 2016. Impact Factor: 2.213. Rank: Q1
  • R. Sharma, A. Dehzangi, J. Lyons, K. Paliwal, T. Tsunoda, and A. Sharma, “Predict Gram-positive and Gram-negative subcellular localization via incorporating evolutionary information and physicochemical features into Chou’s general PseAAC”, IEEE Transactions on Nanobioscience, 2015. Impact Factor: 2.29. Rank: Q2
  • Sharma, R., and Lee, S. R., “A novel container ISO code localization using an object clustering method with OpenCV and Visual Studio application”, International Journal of Image, Graphics and Signal Processing, 2013. Rank: Q4
  • Sharma, R., and Lee, S. R., “Smart ship container with M2M technology”, The Journal of Korea Information and Communications Society, 2013. Rank: Q2
  • Sharma, R., and Lee, S. R., “Application of target point detection technique for positioning and assembling of ship blocks”, International Journal of Advanced Science and Technology, 2013. Rank: Q4

Book and Book Chapters:

  • Abel Chandra, Yosvany López, Iman Dehzangi, Swakkhar Shatabda, Abdul Sattar, Piotr J. Kamola, Ronesh Sharma, Daichi Shigemizu, Tatsuhiko Tsunoda, Alok Sharma, “Advances in Computational Pipelines and Workflows in Bioinformatics” in Reference Module in Life Sciences: Elsevier, 2024.
  • Y. Lopez, P. Kamola, R. Sharma, D. Shigemizu, T. Tsunoda, and A. Sharma, “Computational Pipelines and Workflows in Bioinformatics”, Encyclopedia of Bioinformatics and Computational Biology, ISBN 9780128114148, Elsevier, 2018.

Conference:

  • R. Sharma, T. Tsunoda, and A. Sharma, “An overview of Molecular Recognition of Features prediction”, 11th International Conference on Advanced Engineering and ICT-Convergence, Advanced Engineering and ICT-Convergence Proceedings (AEICP) ISSN: 2635-4586 | Date of Publishing: July 28, 2023. © ICT-Advanced Engineering Society.
  • N. Chandra, S. Kumar, and R. Sharma, “Predictive controller for PWM-driven Variable Speed Drive”, 11th International Conference on Advanced Engineering and ICT-Convergence, Advanced Engineering and ICT-Convergence Proceedings (AEICP) ISSN: 2635-4586 | Date of Publishing: July 28, 2023. © ICT-Advanced Engineering Society.
  • R. Sharma, A. Sharma, A. Patil, and T. Tsunoda, “Discovering MoRFs by trisecting intrinsically disordered protein sequence into terminals and middle regions”, International Conference on Bioinformatics, 2018.
  • R. Sharma, S. Kumar, T. Tsunoda, A. Patil, and A. Sharma, “Predicting MoRFS in Protein Sequence using HMM Profiles”, International Conference on Bioinformatics, 2016.
  • S. Kumar, R. Sharma, A. Sharma, and T. Tsunoda, “Decimation Filter with Common Spatial Pattern and Fisher’s Discriminant Analysis for Motor Imagery Classification”, IEEE World Congress on Computational Intelligence, 2016.
  • A. Sharma, R. Sharma, A. Dehzangi, J. Lyons, K. Paliwal, and T. Tsunoda, “Importance of dimensionality reduction in protein fold recognition”, 2nd Asia-Pacific World Congress on Computer Science and Engineering, pp. 1-6, 2015.
  • Sharma, R., Lee, Y., Kim, B., Kim, Y., Heo, Y., Jeon, H., Kim, K., Lee, S. R., “Auto location and security alert embedded with container identification for real-time applications”, International Conference on ICT Convergence (ICTC), pp. 365-370, 14-16 Oct. 2013.
  • Sharma, R., and Lee, S. R., “Auto location and security alert system for container transportation”, International Conference on Convergence and its Application (ICCA), Seoul, South Korea, Vol. 24, pp. 64–67, 10-11 July 2013.
  • Sharma, R., and Lee, S. R., “Code recognition and identification technology for shipping containers”, General Autumn Conference of Korea Information and Communication Society, pp. 221-222, Seoul, South Korea, Oct. 2012.

Patent: None

Teaching interest:

  • Analog Electronics
  • Digital Electronics
  • Signals and Systems
  • Industrial Electronics
  • Control Systems
  • Advanced Digital Control
  • Digital Signal Processing
  • Engineering Modeling
  • Computing Science
  • Digital Image Processing
  • Bioinformatics
  • Machine Learning
  • Data Mining
  • Pattern Recognition
  • Artificial Intelligence
  • Research Methods

Research interest:

  • Artificial Intelligence
  • Machine Learning Algorithms
  • Bioinformatics
  • Data Mining
  • Pattern Recognition
  • Process Control Engineering