Balachandran Manavalan
Orcid: 0000-0003-0697-9419
According to our database1,
Balachandran Manavalan
authored at least 43 papers
between 2015 and 2025.
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Bibliography
2025
Decision making based ensemble feature selection approach through a new score function in q-rung orthopair hesitant fuzzy environment.
Math. Comput. Simul., 2025
M3S-ALG: Improved and robust prediction of allergenicity of chemical compounds by using a novel multi-step stacking strategy.
Future Gener. Comput. Syst., 2025
REMED-T2D: A robust ensemble learning model for early detection of type 2 diabetes using healthcare dataset.
Comput. Biol. Medicine, 2025
Leveraging deep transfer learning and explainable AI for accurate COVID-19 diagnosis: Insights from a multi-national chest CT scan study.
Comput. Biol. Medicine, 2025
2024
Stack-DHUpred: Advancing the accuracy of dihydrouridine modification sites detection via stacking approach.
Comput. Biol. Medicine, February, 2024
Unveiling local and global conformational changes and allosteric communications in SOD1 systems using molecular dynamics simulation and network analyses.
Comput. Biol. Medicine, January, 2024
HOTGpred: Enhancing human O-linked threonine glycosylation prediction using integrated pretrained protein language model-based features and multi-stage feature selection approach.
Comput. Biol. Medicine, 2024
mHPpred: Accurate identification of peptide hormones using multi-view feature learning.
Comput. Biol. Medicine, 2024
2023
Hybrid data augmentation and deep attention-based dilated convolutional-recurrent neural networks for speech emotion recognition.
Expert Syst. Appl., November, 2023
Advancing the accuracy of SARS-CoV-2 phosphorylation site detection via meta-learning approach.
Briefings Bioinform., November, 2023
ADP-Fuse: A novel two-layer machine learning predictor to identify antidiabetic peptides and diabetes types using multiview information.
Comput. Biol. Medicine, October, 2023
Identification of SH2 domain-containing proteins and motifs prediction by a deep learning method.
Comput. Biol. Medicine, August, 2023
Ensemble feature selection using Bonferroni, OWA and Induced OWA aggregation operators.
Appl. Soft Comput., August, 2023
Comput. Biol. Medicine, July, 2023
PSRQSP: An effective approach for the interpretable prediction of quorum sensing peptide using propensity score representation learning.
Comput. Biol. Medicine, May, 2023
VirPipe: an easy-to-use and customizable pipeline for detecting viral genomes from Nanopore sequencing.
Bioinform., May, 2023
MonkeyNet: A robust deep convolutional neural network for monkeypox disease detection and classification.
Neural Networks, April, 2023
Computational prediction of protein folding rate using structural parameters and network centrality measures.
Comput. Biol. Medicine, March, 2023
SiameseCPP: a sequence-based Siamese network to predict cell-penetrating peptides by contrastive learning.
Briefings Bioinform., January, 2023
SER-Fuse: An Emotion Recognition Application Utilizing Multi-Modal, Multi-Lingual, and Multi-Feature Fusion.
Proceedings of the 12th International Symposium on Information and Communication Technology, 2023
2022
Comput. Biol. Medicine, 2022
SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins.
Comput. Biol. Medicine, 2022
NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides.
Comput. Biol. Medicine, 2022
Amyotrophic lateral sclerosis disease-related mutations disrupt the dimerization of superoxide dismutase 1 - A comparative molecular dynamics simulation study.
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
Briefings Bioinform., 2022
STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction.
Briefings Bioinform., 2022
2021
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
2020
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
2019
Proceedings of the Encyclopedia of Bioinformatics and Computational Biology - Volume 3, 2019
Bioinform., 2019
mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation.
Bioinform., 2019
2017
Bioinform., 2017
2015
Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015