Deep metabolome: Applications of deep learning in metabolomics Y Pomyen, K Wanichthanarak, P Poungsombat, J Fahrmann, D Grapov, ... Computational and Structural Biotechnology Journal 18, 2818-2825, 2020 | 122 | 2020 |
Predicting lupus membranous nephritis using reduced picolinic acid to tryptophan ratio as a urinary biomarker K Anekthanakul, S Manocheewa, K Chienwichai, P Poungsombat, ... Iscience 24 (11), 2021 | 9 | 2021 |
Prolonged egg supplement advances growing child’s growth and gut microbiota S Suta, A Surawit, P Mongkolsucharitkul, B Pinsawas, T Manosan, ... Nutrients 15 (5), 1143, 2023 | 8 | 2023 |
Volatile and non‐volatile compound profiles of commercial sweet pickled mango and its correlation with consumer preference N Indrati, P Sumpavapol, RS Samakradhamrongthai, N Phonsatta, ... International Journal of Food Science & Technology 57 (6), 3760-3770, 2022 | 6 | 2022 |
Metabolic profiles alteration of Southern Thailand traditional sweet pickled mango during the production process N Indrati, N Phonsatta, P Poungsombat, S Khoomrung, P Sumpavapol, ... Frontiers in Nutrition 9, 934842, 2022 | 3 | 2022 |
Quantifying fecal and plasma short-chain fatty acids in healthy Thai individuals W Manokasemsan, N Jariyasopit, P Poungsombat, K Kaewnarin, ... Computational and Structural Biotechnology Journal 23, 2163-2172, 2024 | 2 | 2024 |
42242 Biodiversity of feet microbiome in patients with pitted keratolysis: correlation with pitted score and unpleasant odor severity S Yenyuwadee, C Leeyaphan, S Bunyaratavej, P Pattanaprichakul, ... Journal of the American Academy of Dermatology 89 (3), AB129, 2023 | | 2023 |
1459-P: NMR-Based Metabolomics for the Screening of Sleep-Disordered Breathing in Type 2 Diabetes K Lertdetkajorn, P Poungsombat, S Khoomrung, J Phetcharaburanin, ... Diabetes 69 (Supplement_1), 2020 | | 2020 |
Shotgun Sequencing of Southern Thailand Traditional Sweet Pickled Mango During the Production Process N Indrati, W Sirisarn, J Nuanpirom, P Yodsawat, W Wanna, P Prombutara, ... Available at SSRN 4363152, 0 | | |
Screening of non-cytotoxic membrane penetrating peptides using machine learning approach P Poungsombat, W Nawae, M Ruengjitchatchawalya | | |