Balachandran Manavalan

According to our database1, Balachandran Manavalan authored at least 20 papers between 2015 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 




FRTpred: A novel approach for accurate prediction of protein folding rate and type.
Comput. Biol. Medicine, 2022

SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins.
Comput. Biol. Medicine, 2022

Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2.
Briefings Bioinform., 2022

iACVP: markedly enhanced identification of anti-coronavirus peptides using a dataset-specific word2vec model.
Briefings Bioinform., 2022

TACOS: a novel approach for accurate prediction of cell-specific long noncoding RNAs subcellular localization.
Briefings Bioinform., 2022

Accelerating bioactive peptide discovery via mutual information-based meta-learning.
Briefings Bioinform., 2022

STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction.
Briefings Bioinform., 2022

BERT4Bitter: a bidirectional encoder representations from transformers (BERT)-based model for improving the prediction of bitter peptides.
Bioinform., 2021

Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework.
Briefings Bioinform., 2021

Meta-i6mA: an interspecies predictor for identifying DNA N6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine-learning framework.
Briefings Bioinform., 2021

StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides.
Briefings Bioinform., 2021

Integrative machine learning framework for the identification of cell-specific enhancers from the human genome.
Briefings Bioinform., 2021

NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning.
Briefings Bioinform., 2021

HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation.
Bioinform., 2020

Empirical comparison and analysis of web-based cell-penetrating peptide prediction tools.
Briefings Bioinform., 2020

Protein-Carbohydrate Interactions.
Proceedings of the Encyclopedia of Bioinformatics and Computational Biology - Volume 3, 2019

Iterative feature representations improve N4-methylcytosine site prediction.
Bioinform., 2019

mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation.
Bioinform., 2019

SVMQA: support-vector-machine-based protein single-model quality assessment.
Bioinform., 2017

Structure-based protein folding type classification and folding rate prediction.
Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015