| HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation MM Hasan, N Schaduangrat, S Basith, G Lee, W Shoombuatong, ... Bioinformatics 36 (11), 3350-3356, 2020 | 101 | 2020 |
| ACPred: a computational tool for the prediction and analysis of anticancer peptides N Schaduangrat, C Nantasenamat, V Prachayasittikul, W Shoombuatong Molecules 24 (10), 1973, 2019 | 77 | 2019 |
| SCMCRYS: predicting protein crystallization using an ensemble scoring card method with estimating propensity scores of P-collocated amino acid pairs P Charoenkwan, W Shoombuatong, HC Lee, J Chaijaruwanich, ... PloS one 8 (9), e72368, 2013 | 73 | 2013 |
| Unraveling the bioactivity of anticancer peptides as deduced from machine learning W Shoombuatong, N Schaduangrat, C Nantasenamat EXCLI journal 17, 734, 2018 | 70 | 2018 |
| HemoPred: a web server for predicting the hemolytic activity of peptides TS Win, AA Malik, V Prachayasittikul, JE S Wikberg, C Nantasenamat, ... Future medicinal chemistry 9 (3), 275-291, 2017 | 55 | 2017 |
| Meta-iAVP: a sequence-based meta-predictor for improving the prediction of antiviral peptides using effective feature representation N Schaduangrat, C Nantasenamat, V Prachayasittikul, W Shoombuatong International journal of molecular sciences 20 (22), 5743, 2019 | 52 | 2019 |
| i6mA-Fuse: improved and robust prediction of DNA 6 mA sites in the Rosaceae genome by fusing multiple feature representation M Hasan, B Manavalan, W Shoombuatong, M Khatun, H Kurata Plant molecular biology 103 (1), 225-234, 2020 | 49 | 2020 |
| Computer-aided drug design of bioactive natural products V Prachayasittikul, A Worachartcheewan, W Shoombuatong, ... Current Topics in Medicinal Chemistry 15 (18), 1780-1800, 2015 | 49 | 2015 |
| iQSP: A Sequence-Based Tool for the Prediction and Analysis of Quorum Sensing Peptides Using Informative Physicochemical Properties P Charoenkwan, N Schaduangrat, C Nantasenamat, T Piacham, ... International Journal of Molecular Sciences 21 (1), 75, 2019 | 46 | 2019 |
| PAAP: A web server for predicting antihypertensive activity of peptides TS Win, N Schaduangrat, V Prachayasittikul, C Nantasenamat, ... Future medicinal chemistry 10 (15), 1749-1767, 2018 | 45 | 2018 |
| THPep: a machine learning-based approach for predicting tumor homing peptides W Shoombuatong, N Schaduangrat, R Pratiwi, C Nantasenamat Computational Biology and Chemistry 80, 441-451, 2019 | 44 | 2019 |
| iBitter-SCM: Identification and characterization of bitter peptides using a scoring card method with propensity scores of dipeptides P Charoenkwan, J Yana, N Schaduangrat, C Nantasenamat, MM Hasan, ... Genomics 112 (4), 2813-2822, 2020 | 43 | 2020 |
| Predicting metabolic syndrome using the random forest method A Worachartcheewan, W Shoombuatong, P Pidetcha, W Nopnithipat, ... The Scientific World Journal 2015, 2015 | 43 | 2015 |
| i4mC-Mouse: Improved identification of DNA N4-methylcytosine sites in the mouse genome using multiple encoding schemes MM Hasan, B Manavalan, W Shoombuatong, MS Khatun, H Kurata Computational and structural biotechnology journal 18, 906-912, 2020 | 40 | 2020 |
| Probing the origins of human acetylcholinesterase inhibition via QSAR modeling and molecular docking S Simeon, N Anuwongcharoen, W Shoombuatong, AA Malik, ... PeerJ 4, e2322, 2016 | 40 | 2016 |
| Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation P Charoenkwan, C Nantasenamat, M Hasan, W Shoombuatong Journal of Computer-Aided Molecular Design 34 (10), 1105-1116, 2020 | 38 | 2020 |
| CryoProtect: a web server for classifying antifreeze proteins from nonantifreeze proteins R Pratiwi, AA Malik, N Schaduangrat, V Prachayasittikul, JES Wikberg, ... Journal of Chemistry 2017, 2017 | 37 | 2017 |
| HIV-1 CRF01_AE coreceptor usage prediction using kernel methods based logistic model trees W Shoombuatong, S Hongjaisee, F Barin, J Chaijaruwanich, T Samleerat Computers in Biology and Medicine 42 (9), 885-889, 2012 | 37 | 2012 |
| TargetAntiAngio: a sequence-based tool for the prediction and analysis of anti-angiogenic peptides V Laengsri, C Nantasenamat, N Schaduangrat, P Nuchnoi, ... International Journal of Molecular Sciences 20 (12), 2950, 2019 | 36 | 2019 |
| iUmami-SCM: a novel sequence-based predictor for prediction and analysis of umami peptides using a scoring card method with propensity scores of dipeptides P Charoenkwan, J Yana, C Nantasenamat, MM Hasan, W Shoombuatong Journal of Chemical Information and Modeling 60 (12), 6666-6678, 2020 | 34 | 2020 |
