Watshara Shoombuatong
Orcid: 0000-0002-3394-8709
According to our database1,
Watshara Shoombuatong
authored at least 31 papers
between 2011 and 2023.
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Bibliography
2023
DeepAR: a novel deep learning-based hybrid framework for the interpretable prediction of androgen receptor antagonists.
J. Cheminformatics, December, 2023
StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens.
BMC Bioinform., December, 2023
TIPred: a novel stacked ensemble approach for the accelerated discovery of tyrosinase inhibitory peptides.
BMC Bioinform., December, 2023
MMPatho: Leveraging Multilevel Consensus and Evolutionary Information for Enhanced Missense Mutation Pathogenic Prediction.
J. Chem. Inf. Model., November, 2023
PSRQSP: An effective approach for the interpretable prediction of quorum sensing peptide using propensity score representation learning.
Comput. Biol. Medicine, May, 2023
PSRTTCA: A new approach for improving the prediction and characterization of tumor T cell antigens using propensity score representation learning.
Comput. Biol. Medicine, 2023
2022
Improved prediction and characterization of blood-brain barrier penetrating peptides using estimated propensity scores of dipeptides.
J. Comput. Aided Mol. Des., 2022
DeepDNAbP: A deep learning-based hybrid approach to improve the identification of deoxyribonucleic acid-binding proteins.
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
2021
StackHCV: a web-based integrative machine-learning framework for large-scale identification of hepatitis C virus NS5B inhibitors.
J. Comput. Aided Mol. Des., 2021
IRC-Fuse: improved and robust prediction of redox-sensitive cysteine by fusing of multiple feature representations.
J. Comput. Aided Mol. Des., 2021
Comput. Biol. Medicine, 2021
BERT4Bitter: a bidirectional encoder representations from transformers (BERT)-based model for improving the prediction of bitter peptides.
Bioinform., 2021
StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides.
Briefings Bioinform., 2021
NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning.
Briefings Bioinform., 2021
2020
iUmami-SCM: A Novel Sequence-Based Predictor for Prediction and Analysis of Umami Peptides Using a Scoring Card Method with Propensity Scores of Dipeptides.
J. Chem. Inf. Model., 2020
HCVpred : A web server for predicting the bioactivity of hepatitis C virus NS5B inhibitors.
J. Comput. Chem., 2020
ProIn-Fuse: improved and robust prediction of proinflammatory peptides by fusing of multiple feature representations.
J. Comput. Aided Mol. Des., 2020
Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation.
J. Comput. Aided Mol. Des., 2020
HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation.
Bioinform., 2020
2019
Correction to: ThalPred: a web-based prediction tool for discriminating thalassemia trait and ron deficiency anemia.
BMC Medical Informatics Decis. Mak., 2019
ThalPred: a web-based prediction tool for discriminating thalassemia trait and iron deficiency anemia.
BMC Medical Informatics Decis. Mak., 2019
Comput. Biol. Chem., 2019
Comput. Biol. Chem., 2019
2017
AnkPlex: algorithmic structure for refinement of near-native ankyrin-protein docking.
BMC Bioinform., 2017
2016
J. Cheminformatics, 2016
2015
Sequence based human leukocyte antigen gene prediction using informative physicochemical properties.
Int. J. Data Min. Bioinform., 2015
2013
Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2013
2012
HIV-1 CRF01_AE coreceptor usage prediction using kernel methods based logistic model trees.
Comput. Biol. Medicine, 2012
2011
Prediction of the disulphide bonding state of cysteines in proteins using Conditional Random Fields.
Int. J. Data Min. Bioinform., 2011