Prediction of the disulphide bonding state of cysteines in proteins using Conditional Random Fields. - Watshara Shoombuatong; Patrinee Traisathit; Sukon Prasitwattanaseree; Chatchai Tayapiwatana; Robert W. Cutler; Jeerayut Chaijaruwanich (Int. J. Data Min. Bioinform., 2011)

HIV-1 CRF01_AE coreceptor usage prediction using kernel methods based logistic model trees. - Watshara Shoombuatong; Sayamon Hongjaisee; Francis Barin; Jeerayut Chaijaruwanich; Tanawan Samleerat (Comput. Biol. Medicine, 2012)

Predicting protein crystallization using a simple scoring card method. - Watshara Shoombuatong; Hui-Ling Huang; Jeerayut Chaijaruwanich; Phasit Charoenkwan; Hua-Chin Lee; Shinn-Ying Ho (CIBCB, 2013)

Sequence based human leukocyte antigen gene prediction using informative physicochemical properties. - Watshara Shoombuatong; Panuwat Mekha; Jeerayut Chaijaruwanich (Int. J. Data Min. Bioinform., 2015)

osFP: a web server for predicting the oligomeric states of fluorescent proteins. - Saw Simeon; Watshara Shoombuatong; Nuttapat Anuwongcharoen; Likit Preeyanon; Virapong Prachayasittikul; Jarl E. S. Wikberg; Chanin Nantasenamat (J. Cheminformatics, 2016)

AnkPlex: algorithmic structure for refinement of near-native ankyrin-protein docking. - Tanchanok Wisitponchai; Watshara Shoombuatong; Vannajan Sanghiran Lee; Kuntida Kitidee; Chatchai Tayapiwatana (BMC Bioinform., 2017)

HIVCoR: A sequence-based tool for predicting HIV-1 CRF01_AE coreceptor usage. - Sayamon Hongjaisee; Chanin Nantasenamat; Tanawan Samleerat Carraway; Watshara Shoombuatong (Comput. Biol. Chem., 2019)

THPep: A machine learning-based approach for predicting tumor homing peptides. - Watshara Shoombuatong; Nalini Schaduangrat; Reny Pratiwi; Chanin Nantasenamat (Comput. Biol. Chem., 2019)

ThalPred: a web-based prediction tool for discriminating thalassemia trait and iron deficiency anemia. - Vishuda Laengsri; Watshara Shoombuatong; W. Adirojananon; C. Nantasenamart; Virapong Prachayasittikul; Pornlada Nuchnoi (BMC Medical Informatics Decis. Mak., 2019)

Correction to: ThalPred: a web-based prediction tool for discriminating thalassemia trait and ron deficiency anemia. - Vishuda Laengsri; Watshara Shoombuatong; W. Adirojananon; Chanin Nantasenamat; Virapong Prachayasittikul; Pornlada Nuchnoi (BMC Medical Informatics Decis. Mak., 2019)

HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation. - Md. Mehedi Hasan 002; Nalini Schaduangrat; Shaherin Basith; Gwang Lee; Watshara Shoombuatong; Balachandran Manavalan (Bioinform., 2020)

Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation. - Phasit Charoenkwan; Chanin Nantasenamat; Md. Mehedi Hasan 002; Watshara Shoombuatong (J. Comput. Aided Mol. Des., 2020)

ProIn-Fuse: improved and robust prediction of proinflammatory peptides by fusing of multiple feature representations. - Mst. Shamima Khatun; Md. Mehedi Hasan 002; Watshara Shoombuatong; Hiroyuki Kurata (J. Comput. Aided Mol. Des., 2020)

HCVpred : A web server for predicting the bioactivity of hepatitis C virus NS5B inhibitors. - Aijaz Ahmad Malik; Chuleeporn Phanus-umporn; Nalini Schaduangrat; Watshara Shoombuatong; Chartchalerm Isarankura-Na-Ayudhya; Chanin Nantasenamat (J. Comput. Chem., 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. - Phasit Charoenkwan; Janchai Yana; Chanin Nantasenamat; Md. Mehedi Hasan 002; Watshara Shoombuatong (J. Chem. Inf. Model., 2020)

NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning. - Md. Mehedi Hasan 002; Md. Ashad Alam; Watshara Shoombuatong; Hong-Wen Deng; Balachandran Manavalan; Hiroyuki Kurata (Briefings Bioinform., 2021)

StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides. - Phasit Charoenkwan; Wararat Chiangjong; Chanin Nantasenamat; Md. Mehedi Hasan 002; Balachandran Manavalan; Watshara Shoombuatong (Briefings Bioinform., 2021)

BERT4Bitter: a bidirectional encoder representations from transformers (BERT)-based model for improving the prediction of bitter peptides. - Phasit Charoenkwan; Chanin Nantasenamat; Md. Mehedi Hasan 002; Balachandran Manavalan; Watshara Shoombuatong (Bioinform., 2021)

Effects of Bacille Calmette Guerin (BCG) vaccination during COVID-19 infection. - Utpala Nanda Chowdhury; Md. Omar Faruqe; Md Mehedy; Shamim Ahmad; M. Babul Islam; Watshara Shoombuatong; A. K. M. Azad; Mohammad Ali Moni (Comput. Biol. Medicine, 2021)

IRC-Fuse: improved and robust prediction of redox-sensitive cysteine by fusing of multiple feature representations. - Md. Mehedi Hasan 002; Md. Ashad Alam; Watshara Shoombuatong; Hiroyuki Kurata (J. Comput. Aided Mol. Des., 2021)

StackHCV: a web-based integrative machine-learning framework for large-scale identification of hepatitis C virus NS5B inhibitors. - Aijaz Ahmad Malik; Warot Chotpatiwetchkul; Chuleeporn Phanus-umporn; Chanin Nantasenamat; Phasit Charoenkwan; Watshara Shoombuatong (J. Comput. Aided Mol. Des., 2021)

NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides. - Phasit Charoenkwan; Nalini Schaduangrat; Pietro Lio'; Mohammad Ali Moni; Balachandran Manavalan; Watshara Shoombuatong (Comput. Biol. Medicine, 2022)

SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins. - Phasit Charoenkwan; Nalini Schaduangrat; Mohammad Ali Moni; Pietro Lio'; Balachandran Manavalan; Watshara Shoombuatong (Comput. Biol. Medicine, 2022)

DeepDNAbP: A deep learning-based hybrid approach to improve the identification of deoxyribonucleic acid-binding proteins. - Md. Faruk Hosen; S. M. Hasan Mahmud; Kawsar Ahmed; Wenyu Chen; Mohammad Ali Moni; Hong-Wen Deng; Watshara Shoombuatong; Md. Mehedi Hasan 002 (Comput. Biol. Medicine, 2022)

Improved prediction and characterization of blood-brain barrier penetrating peptides using estimated propensity scores of dipeptides. - Phasit Charoenkwan; Pramote Chumnanpuen; Nalini Schaduangrat; Pietro Lio'; Mohammad Ali Moni; Watshara Shoombuatong (J. Comput. Aided Mol. Des., 2022)

PSRTTCA: A new approach for improving the prediction and characterization of tumor T cell antigens using propensity score representation learning. - Phasit Charoenkwan; Chonlatip Pipattanaboon; Chanin Nantasenamat; Md. Mehedi Hasan 002; Mohammad Ali Moni; Pietro Lio'; Watshara Shoombuatong (Comput. Biol. Medicine, 2023)

PSRQSP: An effective approach for the interpretable prediction of quorum sensing peptide using propensity score representation learning. - Phasit Charoenkwan; Pramote Chumnanpuen; Nalini Schaduangrat; Changmin Oh; Balachandran Manavalan; Watshara Shoombuatong (Comput. Biol. Medicine, 2023)

MMPatho: Leveraging Multilevel Consensus and Evolutionary Information for Enhanced Missense Mutation Pathogenic Prediction. - Fang Ge; Muhammad Arif 012; Zihao Yan; Hanin H. Alahmadi; Apilak Worachartcheewan; Dong-Jun Yu; Watshara Shoombuatong (J. Chem. Inf. Model., 2023)

TIPred: a novel stacked ensemble approach for the accelerated discovery of tyrosinase inhibitory peptides. - Phasit Charoenkwan; Sasikarn Kongsompong; Nalini Schaduangrat; Pramote Chumnanpuen; Watshara Shoombuatong (BMC Bioinform., 2023)

StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens. - Phasit Charoenkwan; Nalini Schaduangrat; Watshara Shoombuatong (BMC Bioinform., 2023)

DeepAR: a novel deep learning-based hybrid framework for the interpretable prediction of androgen receptor antagonists. - Nalini Schaduangrat; Nuttapat Anuwongcharoen; Phasit Charoenkwan; Watshara Shoombuatong (J. Cheminformatics, 2023)

The role of ncRNA regulatory mechanisms in diseases - case on gestational diabetes. - Dong Gao; Liping Ren; Yu-Duo Hao; Nalini Schaduangrat; Xiao-Wei Liu; Shi-Shi Yuan; Yu-He Yang; Yan Wang; Watshara Shoombuatong; Hui Ding (Briefings Bioinform., 2024)

A comprehensive review and evaluation of machine learning-based approaches for identifying tumor T cell antigens. - Watshara Shoombuatong; Saeed Ahmed; S. M. Hasan Mahmud; Nalini Schaduangrat (Comput. Biol. Chem., 2025)

M3S-ALG: Improved and robust prediction of allergenicity of chemical compounds by using a novel multi-step stacking strategy. - Phasit Charoenkwan; Nalini Schaduangrat; Le Thi Phan; Balachandran Manavalan; Watshara Shoombuatong (Future Gener. Comput. Syst., 2025)

M3S-GRPred: a novel ensemble learning approach for the interpretable prediction of glucocorticoid receptor antagonists using a multi-step stacking strategy. - Nalini Schaduangrat; Hathaichanok Chuntakaruk; Thanyada Rungrotmongkol; Pakpoom Mookdarsanit; Watshara Shoombuatong (BMC Bioinform., 2025)