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Watshara Shoombuatong
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2020 – today
- 2025
- [j31]Phasit Charoenkwan, Nalini Schaduangrat, Le Thi Phan, Balachandran Manavalan
, Watshara Shoombuatong
M3S-ALG: Improved and robust prediction of allergenicity of chemical compounds by using a novel multi-step stacking strategy. Future Gener. Comput. Syst. 162: 107455 (2025) - 2023
- [j30]Phasit Charoenkwan, Nalini Schaduangrat, Watshara Shoombuatong:
StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens. BMC Bioinform. 24(1): 301 (2023) - [j29]Phasit Charoenkwan, Sasikarn Kongsompong, Nalini Schaduangrat, Pramote Chumnanpuen, Watshara Shoombuatong:
TIPred: a novel stacked ensemble approach for the accelerated discovery of tyrosinase inhibitory peptides. BMC Bioinform. 24(1): 356 (2023) - [j28]Phasit Charoenkwan, Chonlatip Pipattanaboon, Chanin Nantasenamat, Md. Mehedi Hasan, Mohammad Ali Moni
PSRTTCA: A new approach for improving the prediction and characterization of tumor T cell antigens using propensity score representation learning. Comput. Biol. Medicine 152: 106368 (2023) - [j27]Phasit Charoenkwan, Pramote Chumnanpuen
PSRQSP: An effective approach for the interpretable prediction of quorum sensing peptide using propensity score representation learning. Comput. Biol. Medicine 158: 106784 (2023) - [j26]Nalini Schaduangrat, Nuttapat Anuwongcharoen, Phasit Charoenkwan, Watshara Shoombuatong:
DeepAR: a novel deep learning-based hybrid framework for the interpretable prediction of androgen receptor antagonists. J. Cheminformatics 15(1): 50 (2023) - [j25]Fang Ge, Muhammad Arif
MMPatho: Leveraging Multilevel Consensus and Evolutionary Information for Enhanced Missense Mutation Pathogenic Prediction. J. Chem. Inf. Model. 63(22): 7239-7257 (2023) - 2022
- [j24]Md. Faruk Hosen
DeepDNAbP: A deep learning-based hybrid approach to improve the identification of deoxyribonucleic acid-binding proteins. Comput. Biol. Medicine 145: 105433 (2022) - [j23]Phasit Charoenkwan
SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins. Comput. Biol. Medicine 146: 105704 (2022) - [j22]Phasit Charoenkwan
NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides. Comput. Biol. Medicine 148: 105700 (2022) - [j21]Phasit Charoenkwan, Pramote Chumnanpuen
Improved prediction and characterization of blood-brain barrier penetrating peptides using estimated propensity scores of dipeptides. J. Comput. Aided Mol. Des. 36(11): 781-796 (2022) - 2021
- [j20]Md. Mehedi Hasan
NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning. Briefings Bioinform. 22(6) (2021) - [j19]Phasit Charoenkwan, Wararat Chiangjong, Chanin Nantasenamat, Md. Mehedi Hasan
StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides. Briefings Bioinform. 22(6) (2021) - [j18]Phasit Charoenkwan, Chanin Nantasenamat, Md. Mehedi Hasan
BERT4Bitter: a bidirectional encoder representations from transformers (BERT)-based model for improving the prediction of bitter peptides. Bioinform. 37(17): 2556-2562 (2021) - [j17]Utpala Nanda Chowdhury
Effects of Bacille Calmette Guerin (BCG) vaccination during COVID-19 infection. Comput. Biol. Medicine 138: 104891 (2021) - [j16]Md. Mehedi Hasan
IRC-Fuse: improved and robust prediction of redox-sensitive cysteine by fusing of multiple feature representations. J. Comput. Aided Mol. Des. 35(3): 315-323 (2021) - [j15]Aijaz Ahmad Malik, Warot Chotpatiwetchkul
StackHCV: a web-based integrative machine-learning framework for large-scale identification of hepatitis C virus NS5B inhibitors. J. Comput. Aided Mol. Des. 35(10): 1037-1053 (2021) - 2020
- [j14]Md. Mehedi Hasan
HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation. Bioinform. 36(11): 3350-3356 (2020) - [j13]Phasit Charoenkwan, Chanin Nantasenamat
Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation. J. Comput. Aided Mol. Des. 34(10): 1105-1116 (2020) - [j12]Mst. Shamima Khatun, Md. Mehedi Hasan
ProIn-Fuse: improved and robust prediction of proinflammatory peptides by fusing of multiple feature representations. J. Comput. Aided Mol. Des. 34(12): 1229-1236 (2020) - [j11]Aijaz Ahmad Malik, Chuleeporn Phanus-umporn, Nalini Schaduangrat
HCVpred : A web server for predicting the bioactivity of hepatitis C virus NS5B inhibitors. J. Comput. Chem. 41(20): 1820-1834 (2020) - [j10]Phasit Charoenkwan, Janchai Yana
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. 60(12): 6666-6678 (2020)
2010 – 2019
- 2019
- [j9]Sayamon Hongjaisee
HIVCoR: A sequence-based tool for predicting HIV-1 CRF01_AE coreceptor usage. Comput. Biol. Chem. 80: 419-432 (2019) - [j8]Watshara Shoombuatong
THPep: A machine learning-based approach for predicting tumor homing peptides. Comput. Biol. Chem. 80: 441-451 (2019) - [j7]Vishuda Laengsri
ThalPred: a web-based prediction tool for discriminating thalassemia trait and iron deficiency anemia. BMC Medical Informatics Decis. Mak. 19(1): 212:1-212:14 (2019) - [j6]Vishuda Laengsri
Correction to: ThalPred: a web-based prediction tool for discriminating thalassemia trait and ron deficiency anemia. BMC Medical Informatics Decis. Mak. 19(1): 228:1 (2019) - 2017
- [j5]Tanchanok Wisitponchai, Watshara Shoombuatong
AnkPlex: algorithmic structure for refinement of near-native ankyrin-protein docking. BMC Bioinform. 18(1): 220:1-220:12 (2017) - 2016
- [j4]Saw Simeon
osFP: a web server for predicting the oligomeric states of fluorescent proteins. J. Cheminformatics 8(1): 72:1-72:15 (2016) - 2015
- [j3]Watshara Shoombuatong
Sequence based human leukocyte antigen gene prediction using informative physicochemical properties. Int. J. Data Min. Bioinform. 13(3): 211-224 (2015) - 2013
- [c1]Watshara Shoombuatong
Predicting protein crystallization using a simple scoring card method. CIBCB 2013: 23-30 - 2012
- [j2]Watshara Shoombuatong
HIV-1 CRF01_AE coreceptor usage prediction using kernel methods based logistic model trees. Comput. Biol. Medicine 42(9): 885-889 (2012) - 2011
- [j1]Watshara Shoombuatong
Prediction of the disulphide bonding state of cysteines in proteins using Conditional Random Fields. Int. J. Data Min. Bioinform. 5(4): 449-464 (2011)
Coauthor Index
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