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About the College

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  • About the College
  • Faculty
  • Integrative Biotechnology

Faculty - Integrative Biotechnology

  • Assistant Professor Computational Biology
  • BALACHANDRAN, MANAVALAN
    Lab Computational Biology and Bioinformatics

Research Interest

Bioinformatics,
Data Mining,
Machine Learning

Education

  • 2003 Bachelor of Science in Biochemistry (B.S.), University of Madras
  • 2006 Master of Science in Bioinformatics (M.S.), University of Madras
  • 2011 Doctorate in Computational Biology (Ph.D.), Ajou University

Experience

  • November 2011 ~ February 2017: Research fellow, Korea Institute for Advanced Study
  • March 2017 ~ February 2022: Research Assistant Professor, Ajou University School of Medicine
  • Feb 21, 2022 ~ Present: Assistant Professor, Dept of Integrative Biotechnology, Sungkyunkwan University

Journal Articles

  • (2024)  H2Opred: a robust and efficient hybrid deep learning model for predicting 2’-O-methylation sites in human RNA.  BRIEFINGS IN BIOINFORMATICS.  1,  25
  • (2024)  Unveiling local and global conformational changes and allosteric communications in SOD1 systems using molecular dynamics simulation and network analyses.  COMPUTERS IN BIOLOGY AND MEDICINE.  168,  107688
  • (2023)  Stack-DHUpred: Advancing the accuracy of dihydrouridine modification sites detection via stacking approach.  COMPUTERS IN BIOLOGY AND MEDICINE.  1,  15
  • (2023)  Advancing the accuracy of SARS-CoV-2 phosphorylation site detection via meta-learning approach.  BRIEFINGS IN BIOINFORMATICS.  25,  1
  • (2023)  RDR100: A Robust Computational Method for Identification of Krüppellike Factors.  CURRENT BIOINFORMATICS.  1,  25
  • (2023)  ADP-Fuse: A novel two-layer machine learning predictor to identify antidiabetic peptides and diabetes types using multiview information.  COMPUTERS IN BIOLOGY AND MEDICINE.  165,  107386
  • (2023)  Protection of c-Fos from autophagic degradation by PRMT1-mediated methylation fosters gastric tumorigenesis.  INTERNATIONAL JOURNAL OF BIOLOGICAL SCIENCES.  19,  12
  • (2023)  Hybrid data augmentation and deep attention-based dilated convolutional-recurrent neural networks for speech emotion recognition.  EXPERT SYSTEMS WITH APPLICATIONS.  230, 
  • (2023)  Identification of SH2 domain-containing proteins and motifs prediction by a deep learning method.  COMPUTERS IN BIOLOGY AND MEDICINE.  162, 
  • (2023)  Ensemble feature selection using Bonferroni, OWA and Induced OWA aggregation operators.  APPLIED SOFT COMPUTING.  143, 
  • (2023)  VirPipe: an easy and robust pipeline for detecting customized viral genomes obtained by Nanopore sequencing.  BIOINFORMATICS.  1,  3
  • (2023)  DrugormerDTI: Drug Graphormer for drug-target interaction prediction.  COMPUTERS IN BIOLOGY AND MEDICINE.  161,  1
  • (2023)  A comprehensive revisit of the machine-learning tools developed for the identification of enhancers in the human genome.  PROTEOMICS.  23,  13-14
  • (2023)  Pretoria: An effective computational approach for accurate and high-throughput identification of CD8+t-cell epitopes of eukaryotic pathogens.  INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES.  238, 
  • (2023)  How well does a data-driven prediction method distinguish dihydrouridine from tRNA and mRNA?.  MOLECULAR THERAPY-NUCLEIC ACIDS.  31, 
  • (2023)  PSRQSP: An effective approach for the interpretable prediction of quorum sensing peptide using propensity score representation learning.  COMPUTERS IN BIOLOGY AND MEDICINE.  158, 
  • (2023)  MonkeyNet: A robust deep convolutional neural network for monkeypox disease detection and classification.  NEURAL NETWORKS.  161, 
  • (2023)  Computational prediction of protein folding rate using structural parameters and network centrality measures.  COMPUTERS IN BIOLOGY AND MEDICINE.  155, 
  • (2023)  PRR-HyPred: A two-layer hybrid framework to predict pattern recognition receptors and their families by employing sequence encoded optimal features.  INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES.  234, 
  • (2023)  An Effective Integrated Machine Learning Framework for Identifying Severity of Tomato Yellow Leaf Curl Virus and Their Experimental Validation.  RESEARCH.  6,