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 25/12/2021
  • 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.
  • Our work miRNAFinder: A Comprehensive Web Resource for Plant Pre-microRNA Classification is now available as a preprint 
  • Our work on Crop disease detection with Deep learning has been accepted for an oral presentation at iPURSE 2021. Further work on the project is up at https://damayanthiherath.github.io/leaf-disease-classification/
  • We will be organizing a special session on data engineering for biology and medicine at ICIAFS conference 2021.

People

Dr Damayanthi Herath

Dr Asitha Bandaranayake

Collaborators

Testomonials

Contact

damayanthiherath@eng.pdn.ac.lk

Undergraduate Students

Past Students

Software

http://mirnafinder.shyaman.me/

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Publications

2021

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

2020

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.

Presentations/Talks