Heterogeneous ensemble approach with discriminative features and modified-SMOTEbagging for pre-miRNA classification S Lertampaiporn, C Thammarongtham, C Nukoolkit, ... Nucleic acids research 41 (1), e21-e21, 2013 | 80 | 2013 |
Safety Assessment of a Nham Starter Culture Lactobacillus plantarum BCC9546 via Whole-genome Analysis N Chokesajjawatee, P Santiyanont, K Chantarasakha, K Kocharin, ... Scientific reports 10 (1), 10241, 2020 | 58 | 2020 |
Identification of non-coding RNAs with a new composite feature in the Hybrid Random Forest Ensemble algorithm S Lertampaiporn, C Thammarongtham, C Nukoolkit, ... Nucleic acids research 42 (11), e93-e93, 2014 | 52 | 2014 |
Ensemble-AMPPred: robust AMP prediction and recognition using the ensemble learning method with a new hybrid feature for differentiating AMPs S Lertampaiporn, T Vorapreeda, A Hongsthong, C Thammarongtham Genes 12 (2), 137, 2021 | 27 | 2021 |
Ensemble of Multiple Classifiers for multilabel classification of plant protein subcellular localization W Wattanapornprom, C Thammarongtham, A Hongsthong, ... Life 11 (4), 293, 2021 | 15 | 2021 |
PSO-LocBact: a consensus method for optimizing multiple classifier results for predicting the subcellular localization of bacterial proteins S Lertampaiporn, S Nuannimnoi, T Vorapreeda, N Chokesajjawatee, ... BioMed Research International 2019, 2019 | 9 | 2019 |
Safety assessment of a nham starter culture Lactobacillus plantarum BCC9546 via whole-genome analysis. Sci Rep 10: 10241 N Chokesajjawatee, P Santiyanont, K Chantarasakha, K Kocharin, ... | 6 | 2020 |
Ensemble-AHTPpred: A robust ensemble machine learning model integrated with a new composite feature for identifying antihypertensive peptides S Lertampaiporn, A Hongsthong, W Wattanapornprom, ... Frontiers in Genetics 13, 883766, 2022 | 5 | 2022 |
mSRFR: a machine learning model using microalgal signature features for ncRNA classification S Anuntakarun, S Lertampaiporn, T Laomettachit, W Wattanapornprom, ... BioData Mining 15 (1), 8, 2022 | 4 | 2022 |
Improved prediction of eukaryotic protein subcellular localization using particle swarm optimization of multiple classifiers S Nuannimnoi, S Lertampaiporn, C Thammarongtham 2017 21st International Computer Science and Engineering Conference (ICSEC), 1-5, 2017 | 3 | 2017 |
Spirulina-in Silico-Mutations and Their Comparative Analyses in the Metabolomics Scale by Using Proteome-Based Flux Balance Analysis S Lertampaiporn, J Senachak, W Taenkaew, C Khannapho, ... Cells 9 (9), 2097, 2020 | 1 | 2020 |
Weighted Ensemble for Plant Protein Subcellular Localization Using Particle Swarm Optimization W Wattanapornprom, T Glomrit, T Prayongsup, P Suwanthanarat, ... 2021 18th International Conference on Electrical Engineering/Electronics …, 2021 | | 2021 |
Application of Random Forest in Limited Size Human Long Non-coding RNAs Identification with Secondary Structure Features S Anuntakarun, W Wattanapornprom, S Lertampaiporn 2019 23rd International Computer Science and Engineering Conference (ICSEC …, 2019 | | 2019 |
AdaBoost Algorithm with Random Forests for Plant and Animal Precursor MicroRNAs Classification S Anuntakarun, W Wattanapornprom, S Lertampaiporn 2017 21st International Computer Science and Engineering Conference (ICSEC), 1-5, 2017 | | 2017 |
Identification of Plant Precursor miRNAs using Structural Robustness and Secondary Structures Features S Anuntakarun, W Wattanapornprom, S Lertampaiporn Proceedings of the 2017 International Conference on Biomedical Engineering …, 2017 | | 2017 |
Enhanced Viral Precursor MicroRNA Identification with Structural Robustness Features in Back-Propagation Neural Network S Anuntakarun, S Ingsriswang, W Wattanapornprom, S Lertampaiporn 2016 7th International Conference on Intelligent Systems, Modelling and …, 2016 | | 2016 |
Viral MicroRNA Precursors Discovery with Self-containment Index and Derivative Features using Back-propagation Neural Network S Anuntakarun, W Wattanapornprom, S Ingsriswang, S Lertampaiporn | | |