Our Research

Below are our main area of research interest

  • Prediction of DNA regulatory elements such as nucleosome, origin of replications, transcription start sites and promoter.
  • Designing computational method to predict post-transcriptional (RNA) modification sites, RNA subcellular localization and RNA splicing.
  • Designing computational method to predict post-replication (DNA) modification sites.
  • Developing machine learning methods to identify protein function and type.
  • Developing machine learning methods to identify peptide therapeutic function.
  • Simulation of biomolecular systems.

News

Our lab recent news!

  • [Jan-17-2023] Prof.Balachandran was appointed as the Editorial board member of Current Bioinformatics. (IF:4.850)

  • [Jan-13-2023] Prof.Balachandran is now guest editing a special issue in journal Frontiers in Bioscience-Landmark (IF=3.115) focusing on "New Insights into Computational Medicine and Bioinformatics Research". The submission deadline is September 30, 2023. If anyone interested, contact Prof. Balachandran.

  • [Dec-29-2022] Our paper entitled "GPApred: The first computational predictor for identifying proteins with LPXTG-like motif using sequence-based optimal features." has been accepted in International Journal of Biological Macromolecules. (JCR = 6; IF:8.025)

  • [Dec-21-2022] Topic Editor (Overcoming Challenges in Vaccines and Molecular Therapeutics: 2022) in Frontiers in Immunology (IF:8.786) link

  • [Nov-11-2022] Our paper entitled "SiameseCPP: A sequence-based siamese network to predict cell-penetrating peptides by contrastive learning." has been published in Briefings in Bioinformatics. (JCR = 1; IF:13.994)

  • [Nov-07-2022] Our paper entitled "An effective integrated machine learning framework for identifying severity of tomato yellow leaf curl virus and their experimental validation." has been published in Research. (JCR = 10; IF:11.036)

  • [Oct-11-2022] Prof. Balachandran has been selected as one of the World's Top 2% highly cited researchers in 2022 ( Stanford data and news).

  • [Jul-29-2022] Our lab's recent published work has been highlighted in SKKU's research stories

  • [Jul-01-2022] Our paper entitled "iACVP: markedly enhanced identification of anti-coronavirus peptides using a dataset-specific word2vec model." has been published in Briefings in Bioinformatics. (JCR=1; Impact factor = 13.994)

  • [Jun-27-2022] Our paper entitled "TACOS: a novel approach for accurate prediction of cell-specific long noncoding RNAs subcellular localization." has been published in Briefings in Bioinformatics. (JCR=1; Impact factor = 13.994)

  • [May-03-2022] Our paper entitled "Deepm5C: A deep learning-based hybrid framework for identifying human RNA N5- methylcytosine sites using a stacking strategy." has been accepted for publication on Molecular Therapy. (JCR = 9; IF:12.910)

  • [May-05-2022] Prof. Balachandran was appointed as the Editorial Board Member of iMeta.

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