As much as there is a universe as we look up, there is a universe to explore within ourselves, at micro level. The computational biology research lab at Department of Computer Engineering, University of Peradeniya focuses on exploring the use of Computer science and Engineering to elucidate the biological systems around us and using that knowledge in various applications.

Recent Updates

Last Updated on 01/03/2022
  • One of our groups work (on miRNA) has been recognised nationally as 1st runners up at Best Research Awards 2021 organised by Institute of Applied Statistics Sri Lanka.
  • Our work miRNAFinder: A Comprehensive Web Resource for Plant Pre-microRNA Classification has been accpeted for publication in Elsevier BioSystems journal.
  • Our work on Accurate plant disease classification with transfer learning based on leaf images has been accepted for the 16th IEEE conference on Industrial and Automation Systems (ICIIS 2021)
  • Our group members will be conducting a workshop on Explainable Machine Learning at ICIIS 2021.
  • Our group members will be inovled in a workshop on Feature Engineering in Machine Learning at ICIET 2021.
  • Our work on Machine Learning for detecting alzhemizers disease using Next Generation Sequencing Data has been accepted for the IEEE International Conference on Industrial and Financial Automation Systems (ICIAFS ) 2021
  • We have been awarded a University of Peradeniya Researh Grant to work further on the project “Counting the uncountable : Estimating species richness from metavirome data”
  • Our systematic review titled “Machine learning for plant microRNA prediction: A systematic review” is now available as a preprint.


Dr Damayanthi Herath

Dr Asitha Bandaranayake



Undergraduate Students

Past Students

S.A. Ishini Udara Sangarasekara

Tharmapalan Thanujan

Aminda Amarasinghe


Imesh Ekanayake

Hasini Thilakarathne

Vidwa Sripadi

Imalsha Dinuwanthi

Hans Thisanke

Chamli Deshan

Supun Darshana


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  Article Remarks
J Machine learning for plant microRNA prediction: A systematic review  

Herath, D., Counting the Uncountable: Estimating Species Diversity

measures of communities of viruses, Hantana Vision Magazine, Volume 7, Issue 1

J Mirnafinder: A comprehensive web resource for plant mirna classfiication, BioSystems Journal Submitted
C Revealing MicroRNA Biomarkers for Alzheimer’s Disease Using Next Generation Sequencing Data ICIAFS 2021-Special Session on Data Engineering for Biology
  Article Remarks
C Ihalagedara, P., Lokuge, S., Jayasundara, S., Herath, D.
and Kahanda, I., 2020, October. miRNAFinder: A pre-microRNA
classi er for plants and analysis of feature impact. In 2020
IEEE Conference on Computational Intelligence in Bioinformatics
and Computational Biology (CIBCB) (pp. 1-7). IEEE.
C Ekanayake, I.U. and Herath, D., 2020, July. Chronic Kidney
Disease Prediction Using Machine Learning Methods.
In 2020 Moratuwa Engineering
Research Conference (MERCon) (pp. 260-265). IEEE.
C Vimukthi, K., Wimalasiri, G., Bandara, P. and Herath, D., 2020, July.
A Data Driven Binning Method to Recover More Nucleotide
Sequences of Species in a Metagenome.
In 2020 Moratuwa Engineering Research Conference (MERCon)
(pp. 307-312). IEEE.
C Perera, S., Hewage, K., Gunarathne, C., Navarathna, R., Herath, D.
and Ragel, R.G., 2020, July. Detection of Novel Biomarker Genes of
Alzheimer’s Disease Using Gene Expression Data.
In 2020 Moratuwa Engineering Research Conference (MERCon)
(pp. 1-6). IEEE.