{"id":36761,"date":"2025-04-18T17:36:49","date_gmt":"2025-04-18T10:36:49","guid":{"rendered":"https:\/\/1dddev.com\/zoosci\/?post_type=ku-personnel&#038;p=36761"},"modified":"2025-04-18T17:45:06","modified_gmt":"2025-04-18T10:45:06","slug":"%e0%b8%a3%e0%b8%a8-%e0%b8%94%e0%b8%a3-%e0%b8%9b%e0%b8%a3%e0%b8%b2%e0%b9%82%e0%b8%a1%e0%b8%97%e0%b8%a2%e0%b9%8c-%e0%b8%8a%e0%b8%b3%e0%b8%99%e0%b8%b2%e0%b8%8d%e0%b8%9b%e0%b8%b7%e0%b8%99","status":"publish","type":"ku-personnel","link":"https:\/\/1dddev.com\/zoosci\/ku-personnel\/%e0%b8%a3%e0%b8%a8-%e0%b8%94%e0%b8%a3-%e0%b8%9b%e0%b8%a3%e0%b8%b2%e0%b9%82%e0%b8%a1%e0%b8%97%e0%b8%a2%e0%b9%8c-%e0%b8%8a%e0%b8%b3%e0%b8%99%e0%b8%b2%e0%b8%8d%e0%b8%9b%e0%b8%b7%e0%b8%99\/","title":{"rendered":"\u0e23\u0e28.\u0e14\u0e23.\u0e1b\u0e23\u0e32\u0e42\u0e21\u0e17\u0e22\u0e4c \u0e0a\u0e33\u0e19\u0e32\u0e0d\u0e1b\u0e37\u0e19"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">\u0e1b\u0e23\u0e30\u0e27\u0e31\u0e15\u0e34\u0e01\u0e32\u0e23\u0e28\u0e36\u0e01\u0e29\u0e32<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u0e01\u0e28.\u0e1a (\u0e27\u0e34\u0e17\u0e22\u0e32\u0e28\u0e32\u0e2a\u0e15\u0e23\u0e4c-\u0e0a\u0e35\u0e27\u0e27\u0e34\u0e17\u0e22\u0e32) \u0e21\u0e2b\u0e32\u0e27\u0e34\u0e17\u0e22\u0e32\u0e25\u0e31\u0e22\u0e28\u0e23\u0e35\u0e19\u0e04\u0e23\u0e34\u0e19\u0e17\u0e23\u0e27\u0e34\u0e42\u0e23\u0e12, \u0e1b\u0e23\u0e30\u0e40\u0e17\u0e28\u0e44\u0e17\u0e22 2546<\/li>\n\n\n\n<li>M.Sc. (Cell and Molecular Biology) \u0e21\u0e2b\u0e32\u0e27\u0e34\u0e17\u0e22\u0e32\u0e25\u0e31\u0e22\u0e40\u0e01\u0e29\u0e15\u0e23\u0e28\u0e32\u0e2a\u0e15\u0e23\u0e4c, \u0e1b\u0e23\u0e30\u0e40\u0e17\u0e28\u0e44\u0e17\u0e22 2549<\/li>\n\n\n\n<li>Ph.D. (Bioscience) Chalmers University of Technology, Sweden 2555<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Our Bioinformatic Tools (Webserver) for Bioactive Peptide Prediction<\/h2>\n\n\n\n<ol class=\"wp-block-list\">\n<li><a href=\"http:\/\/pmlabstack.pythonanywhere.com\/TIPred\" target=\"_blank\" rel=\"noreferrer noopener\">TIPred: a novel stacked ensemble approach for the accelerated discovery of tyrosinase inhibitory peptides\u00a0<\/a><strong><a href=\"http:\/\/pmlabstack.pythonanywhere.com\/TIPred\"><\/a><\/strong><\/li>\n\n\n\n<li><a href=\"TROLLOPE: A novel sequence-based stacked approach for the accelerated discovery of linear T-cell epitopes of hepatitis C virus\" target=\"_blank\" rel=\"noreferrer noopener\">TROLLOPE: A novel sequence-based stacked approach for the accelerated discovery of linear T-cell epitopes of hepatitis C virus\u00a0<\/a><strong><a href=\"http:\/\/pmlabqsar.pythonanywhere.com\/TROLLOPE\"><\/a><\/strong><\/li>\n\n\n\n<li><a href=\"https:\/\/pmlabstack.pythonanywhere.com\/PSRQSP\" target=\"_blank\" rel=\"noreferrer noopener\">PSRQSP: An effective approach for the interpretable prediction of quorum sensing peptide using propensity score representation learning<\/a><strong><a href=\"https:\/\/pmlabstack.pythonanywhere.com\/PSRQSP\"><\/a><\/strong><\/li>\n\n\n\n<li><a href=\"https:\/\/pmlabstack.pythonanywhere.com\/iAMAP-SCM\" target=\"_blank\" rel=\"noreferrer noopener\">iAMAP-SCM: a novel computational tool for large-scale identification of antimalarial peptides using estimated propensity scores of dipeptides\u00a0<\/a><strong><a href=\"https:\/\/pmlabstack.pythonanywhere.com\/iAMAP-SCM\"><\/a><\/strong><\/li>\n\n\n\n<li><a href=\"https:\/\/pmlabstack.pythonanywhere.com\/SCMB3PP\" target=\"_blank\" rel=\"noreferrer noopener\">SCMB3PP:\u00a0Improved prediction and characterization of blood-brain barrier penetrating peptides using estimated propensity scores of dipeptides<\/a>\u00a0<a href=\"https:\/\/pmlabstack.pythonanywhere.com\/SCMB3PP\"><\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/github.com\/Shoombuatong\/MetaNaBP\" target=\"_blank\" rel=\"noreferrer noopener\">MetaNaBP: Leveraging a meta-learning approach to advance the accuracy of Nav blocking peptides prediction\u00a0<\/a><strong><a href=\"https:\/\/github.com\/Shoombuatong\/MetaNaBP\"><\/a><\/strong><\/li>\n\n\n\n<li><a href=\"StackPAP: Accelerating the discovery of plant allergenic proteins using a stacked ensemble-learning framework\" target=\"_blank\" rel=\"noreferrer noopener\">StackPAP: Accelerating the discovery of plant allergenic proteins using a stacked ensemble-learning framework<\/a><\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">\u0e1c\u0e25\u0e07\u0e32\u0e19\u0e41\u0e15\u0e48\u0e07\u0e2b\u0e23\u0e37\u0e2d\u0e40\u0e23\u0e35\u0e22\u0e1a\u0e40\u0e23\u0e35\u0e22\u0e07 \u0e15\u0e33\u0e23\u0e32 \u0e2b\u0e19\u0e31\u0e07\u0e2a\u0e37\u0e2d\u0e2b\u0e23\u0e37\u0e2d\u0e1a\u0e17\u0e04\u0e27\u0e32\u0e21\u0e17\u0e32\u0e07\u0e27\u0e34\u0e0a\u0e32\u0e01\u0e32\u0e23<\/h2>\n\n\n\n<ol class=\"wp-block-list\">\n<li><em><strong>Yeast expression systems for industrial biotechnology<\/strong>. Gene Expression Systems in Fungi: Advancements and Applications. 227-237. Springer International Publishing.<\/em><\/li>\n\n\n\n<li><em><strong>Informatics for Metabolomics.<\/strong>\u00a0Translational Biomedical Informatics, 91-115. Springer Singapore.<\/em><\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">\u0e07\u0e32\u0e19\u0e27\u0e34\u0e08\u0e31\u0e22 \/ \u0e1c\u0e25\u0e07\u0e32\u0e19\u0e15\u0e35\u0e1e\u0e34\u0e21\u0e1e\u0e4c\u0e40\u0e1c\u0e22\u0e41\u0e1e\u0e23\u0e48<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Charoenkwan, P., Kongsompong, S., Schaduangrat, N.,\u00a0<strong>Chumnanpuen, P.<\/strong>, &amp; Shoombuatong, W. (2023). TIPred: a novel stacked ensemble approach for the accelerated discovery of tyrosinase inhibitory peptides.\u00a0<em>BMC bioinformatics<\/em>, 24(1), 356.<\/li>\n\n\n\n<li>Charoenkwan, P., Waramit, S.,\u00a0<strong>Chumnanpuen, P.,<\/strong>\u00a0Schaduangrat, N., &amp; Shoombuatong, W. (2023). TROLLOPE: A novel sequence-based stacked approach for the accelerated discovery of linear T-cell epitopes of hepatitis C virus.\u00a0<em>Plos one<\/em>, 18(8), e0290538.<\/li>\n\n\n\n<li>Nualnisachol, P.,\u00a0<strong>Chumnanpuen, P<\/strong>., &amp; E-kobon, T. (2023). Understanding Snail Mucus Biosynthesis and Shell Biomineralisation through Genomic Data Mining of the Reconstructed Carbohydrate and Glycan Metabolic Pathways of the Giant African Snail (<em>Achatina fulica<\/em>).\u00a0<em>Biology<\/em>, 12(6), 836.<\/li>\n\n\n\n<li>Charoenkwan, P.,\u00a0<strong>Chumnanpuen, P<\/strong>., Schaduangrat, N., Oh, C., Manavalan, B., &amp; Shoombuatong, W. (2023). PSRQSP: An effective approach for the interpretable prediction of quorum sensing peptide using propensity score representation learning.\u00a0<em>Computers in Biology and Medicine<\/em>, 158, 106784.<\/li>\n\n\n\n<li>Kongsompong, S., E-kobon, T., Taengphan, W., Sangkhawasi, M., Khongkow, M., &amp;\u00a0<strong>Chumnanpuen, P.<\/strong>\u00a0(2023). Computer-Aided Virtual Screening and In Vitro Validation of Biomimetic Tyrosinase Inhibitory Peptides from Abalone Peptidome. International Journal of Molecular Sciences, 24(4), 3154.<\/li>\n\n\n\n<li>Prasertsuk, K., Prongfa, K., Suttiwanich, P., Harnkit, N., Sangkhawasi, M., Promta, P., &amp;\u00a0<strong>Chumnanpuen, P.<\/strong>\u00a0(2022). Computer-Aided Screening for Potential Coronavirus 3-Chymotrypsin-like Protease (3CLpro) Inhibitory Peptides from Putative Hemp Seed Trypsinized Peptidome.\u00a0<em>Molecules<\/em>, 28(1), 50.<\/li>\n\n\n\n<li>Hanchanachai, N.,\u00a0<strong>Chumnanpuen, P.,<\/strong>\u00a0E-kobon, T. (2022). Effect of conditioned media from\u00a0<em>Aeromonas caviae<\/em>\u00a0on the transcriptomic changes of the porcine isolates of\u00a0<em>Pasteurella multocida. BMC Microbiology\u00a0<\/em>22 (1), 1-12.<\/li>\n\n\n\n<li>Charoenkwan, P., Schaduangrat, N., Lio, P., Moni, M.A.,\u00a0<strong>Chumnanpuen, P.,<\/strong>\u00a0Shoombuatong, W. (2022). iAMAP-SCM: A Novel Computational Tool for Large-Scale Identification of Antimalarial Peptides Using Estimated Propensity Scores of Dipeptides.\u00a0<em>ACS Omega<\/em>, DOI: 10.1021\/acsomega.2c04465.<\/li>\n\n\n\n<li>Charoenkwan, P.,\u00a0<strong>Chumnanpuen, P<\/strong>., Schaduangrat, N., Lio, P., Moni, M.A., Shoombuatong, W. (2022). Improved prediction and characterization of blood-brain barrier penetrating peptides using estimated propensity scores of dipeptides.\u00a0<em>Journal of Computer-Aided Molecular Design<\/em>, 1-16.<\/li>\n\n\n\n<li>Harnkit, N., Khongsonthi, T., Masuwan, N., Prasartkul, P., Noikaew, T.,\u00a0<strong>Chumnanpuen, P<\/strong>. (2022). Virtual Screening for SARS-CoV-2 Main Protease Inhibitory Peptides from the Putative Hydrolyzed Peptidome of Rice Bran.\u00a0<em>Antibiotics<\/em>\u00a011 (10), 1-15.<\/li>\n\n\n\n<li>Cheawchanlertfa, P., Chitcharoen, S., Raethong, N., Liu, Q.,\u00a0<strong>Chumnanpuen, P.,<\/strong>\u00a0Soommat, P., Song, Y., Koffas, M., Laoteng, K., Vongsangnak, W. (2022). Enhancing Genome-Scale Model by Integrative Exometabolome and Transcriptome: Unveiling Carbon Assimilation towards Sphingolipid Biosynthetic Capability of\u00a0<em>Cordyceps militaris<\/em>.\u00a0<em>Journal of Fungi<\/em>\u00a08 (8), 887.<\/li>\n\n\n\n<li>Srichairat, N., Taksintum, W.,\u00a0<strong>Chumnanpuen, P.<\/strong>\u00a0(2022). Histological and histochemical characteristics of the oral, pharyngeal and accessory digestive organs in the water monitor lizard (<em>Varanus salvator<\/em>) from Thailand.\u00a0<em>Anatomia Histologia Embryologia<\/em>\u00a052, 1-9.<\/li>\n\n\n\n<li>Wattayagorn, V., Kongsema, M., Tadakittisarn, S.,\u00a0<strong>Chumnanpuen, P<\/strong>. (2022) Riceberry Rice Bran Protein Hydrolyzed Fractions Induced Apoptosis, Senescence and G1\/S Cell Cycle Arrest in Human Colon Cancer Cell Lines.\u00a0<em>Applied Sciences<\/em>\u00a012 (14), 6917.<\/li>\n\n\n\n<li>Srichairat, N., Taksintum, W.,\u00a0<strong>Chumnanpuen, P.<\/strong>\u00a0(2022). Histological and histochemical studies of the gastrointestinal tract in the water monitor lizard (<em>Varanus salvator<\/em>).\u00a0<em>Acta Zoologica<\/em>\u00a0103 (3), 376-387.<\/li>\n\n\n\n<li>Fungfuang, W., Pitiporntapin, S.,\u00a0<strong>Chumnanpuen, P.<\/strong>\u00a0Srakaew, N., Chotimanukul, S., Kovitvadhi, U. (2022). Developing of Bachelor Student\u2019s Learning Achievement in Basic Research Methods in Science through Constructivist-based teaching.\u00a0<em>International Journal of Science Educators and Teachers<\/em>\u00a01(1), 32-43.<\/li>\n\n\n\n<li>Chalongkulasak, S., E-kobon, T.,\u00a0<strong>Chumnanpuen, P<\/strong>. (2022). Prediction of Antibacterial Peptides against\u00a0<em>Propionibacterium acnes<\/em>\u00a0from the Peptidomes of\u00a0<em>Achatina fulica\u00a0<\/em>Mucus Fractions.\u00a0<em>Molecules\u00a0<\/em>27 (7), 2290.<\/li>\n\n\n\n<li>Jansong, C., Pitiporntapin, S.,\u00a0<strong>Chumnanpuen, P.,<\/strong>\u00a0Hines, LM., Yokyong, S. (2022). Using socio-scientific issues-based teaching to develop grade 10 students\u2019 informal reasoning skills.\u00a0<em>Kasetsart Journal of Social Sciences<\/em>\u00a043 (1), 217\u2013222.<\/li>\n\n\n\n<li>Chantawannakul, J., Chatpattanasiri, P., Wattayagorn, V., Kongsema, M., Noikaew, T.,\u00a0<strong>Chumnanpuen, P.<\/strong>\u00a0(2021). Virtual Screening for Biomimetic Anti-Cancer Peptides from\u00a0<em>Cordyceps militaris<\/em>\u00a0Putative Pepsinized Peptidome and Validation on Colon Cancer Cell Line.\u00a0<em>Molecules<\/em>\u00a026 (19), 5767.<\/li>\n\n\n\n<li>Pasomboon, P.,\u00a0<strong>Chumnanpuen, P<\/strong>., E-kobon, T. (2021). Modified Genome-Scale Metabolic Model of Escherichia coli by Adding Hyaluronic Acid Biosynthesis-Related Enzymes (GLMU2 and HYAD) from\u00a0<em>Pasteurella multocida<\/em>.\u00a0<em>International Journal of Biotechnology and Bioengineering<\/em>\u00a015 (5), 54-58.<\/li>\n\n\n\n<li>Pasomboon, P.,\u00a0<strong>Chumnanpuen, P<\/strong>., E-kobon, T. (2021). Comparison of Hyaluronic Acid Biosynthetic Genes From Different Strains of\u00a0<em>Pasteurella multocida<\/em>.\u00a0<em>Bioinformatics and Biology Insights<\/em>\u00a015, 11779322211027406.<\/li>\n\n\n\n<li>Tachapuripunya, V., Roytrakul, S.,\u00a0<strong>Chumnanpuen, P.<\/strong>\u00a0Teerasak E-kobon. (2021). Unveiling Putative Functions of Mucus Proteins and Their Tryptic Peptides in Seven Gastropod Species Using Comparative Proteomics and Machine Learning-Based Bioinformatics Predictions.\u00a0<em>Molecules<\/em>\u00a026 (11), 3475.<\/li>\n\n\n\n<li>Kongsompong, S., E-kobon, T.,\u00a0<strong>Chumnanpuen, P<\/strong>. (2021) K-Nearest Neighbor and Random Forest-Based Prediction of Putative Tyrosinase Inhibitory Peptides of Abalone\u00a0<em>Haliotis diversicolor<\/em>.\u00a0<em>Molecules<\/em>\u00a026 (12), 3671.<\/li>\n\n\n\n<li>Hanchanachai, N.,\u00a0<strong>Chumnanpuen, P.,<\/strong>\u00a0E-kobon, T. (2021). Interaction study of Pasteurella multocida with culturable aerobic bacteria isolated from porcine respiratory tracts using coculture in conditioned media.\u00a0<em>BMC microbiology<\/em>\u00a021 (1), 1-13.<\/li>\n\n\n\n<li>Nguyen, T. V.,\u00a0<strong>Chumnanpuen, P<\/strong>., Parunyakul, K., Srisuksai, K., Fungfuang, W. (2021). A study of the aphrodisiac properties of Cordyceps militaris in streptozotocin-induced diabetic male rats.\u00a0<em>Veterinary World<\/em>\u00a014 (2), 537.<\/li>\n\n\n\n<li>Azam, F. M., Zamri-Saad, M.,\u00a0 Rahim, R. A.,\u00a0\u00a0<strong>Chumnanpuen, P.,<\/strong>\u00a0 E-Kobon, T.,\u00a0 Othman, S. (2021). Molecular characterisation of the gdha- derivative of Pasteurella multocida b:2. Pertanika Journal of Tropical Agricultural Science 44 (1), 171-192.<\/li>\n\n\n\n<li>Nguantad, S.,\u00a0<strong>Chumnanpuen, P.,<\/strong>\u00a0Thancharoen, A., Vongsangnak, W., Sriboonlert, A. (2020).\u00a0Identification of potential candidate genes involved in the sex determination cascade in an aquatic firefly,\u00a0<em>Sclerotia aquatilis\u00a0<\/em>(Coleoptera, Lampyridae).\u00a0\u00a0<em>Genomics<\/em>\u00a0112 (3): 2590-2602.<\/li>\n\n\n\n<li>Kantawong, F., Jearasakwattana, T., Nira, A., Chewae, J., Sajjamongkol, P., Phothong, P.,\u00a0<strong>Chumnanpuen, P<\/strong>. (2020). PI3K\/Akt signaling involved with osteoinductive effects of\u00a0<em>Achatina fulica<\/em>\u00a0mucus.\u00a0<em>Brazilian Archives of Biology and Technology<\/em>\u00a063: e20180501.<\/li>\n\n\n\n<li>Wongsa, B., Raethong, N.,\u00a0<strong>Chumnanpuen, P<\/strong>., Wong-ekkabut, J., Laoteng, K., Vongsangnak, W. (2020). Alternative metabolic routes in channeling xylose to cordycepin production of\u00a0<em>Cordyceps militaris<\/em>\u00a0identified by comparative transcriptome analysis.\u00a0<em>Genomics<\/em>\u00a0112 (1): 629-636.<\/li>\n\n\n\n<li>Suwannapan, W., Ngankoh, S., E-kobon, T.,\u00a0<strong>Chumnanpuen, P<\/strong>. (2019). Mucous cell distribution and mucus production during early growth periods of the giant African snail (<em>Achatina fulica<\/em>).\u00a0<em>Agriculture and Natural Resources<\/em>\u00a053 (4): 423-428.<\/li>\n\n\n\n<li>Jatuponwiphat, T.,\u00a0<strong>P. Chumnanpuen<\/strong>, S. Othman, T. E-kobon and W. Vongsangnak (2019). Iron-associated protein interaction networks reveal the key functional modules related to survival and virulence of\u00a0<em>Pasteurella multocida<\/em>.\u00a0<em>Microbial Pathogenesis<\/em>\u00a0127: 257-266.<\/li>\n\n\n\n<li>Tongmai, T., Maketon, M.,\u00a0<strong>Chumnanpuen, P<\/strong>. (2018). Prevention potential of\u00a0<em>Cordyceps militaris<\/em>\u00a0aqueous extract against cyclophosphamind-induced mutagenicity and sperm abnormality in rats.\u00a0<em>Agriculture and Natural Resources<\/em>\u00a052(5), 419-423.<\/li>\n\n\n\n<li>Suwannapan, W.,\u00a0<strong>Chumnanpuen, P<\/strong>., &amp; E-kobon, T. (2018). Amplification and bioinformatics analysis of conserved FAD-binding region of L-amino acid oxidase (LAAO) genes in gastropods compared to other organisms.\u00a0<em>Computational and Structural Biotechnology Journal<\/em>\u00a016, 98-107.<\/li>\n\n\n\n<li>Srichairat, N., W. Taksintum,\u00a0<strong>P. Chumnanpuen<\/strong>. (2018).\u00a0Gross Anatomy of Digestive Organs in Water Monitor Lizard\u00a0<em>Varanus salvator<\/em>\u00a0(Squamata: Varanidae).\u00a0<em>Walailak Journal of Science and Technology<\/em>\u00a015 (3).<\/li>\n\n\n\n<li>Muikham, I., N. Srakaew, K. Chatchavalvanich,\u00a0<strong>P. Chumnanpuen<\/strong>.\u00a0 (2017). Microanatomy of the digestive system of Supachai&#8217;s caecilian,\u00a0<em>Ichthyophis supachaii<\/em>\u00a0Taylor, 1960 (Amphibia: Gymnophiona).\u00a0<em>Acta Zoologica<\/em>\u00a098 (3), 252-270<\/li>\n\n\n\n<li>Vongsangnak, W.,\u00a0<strong>P. Chumnanpuen<\/strong>, A. Sriboonlert. (2016). Transcriptome analysisreveals candidate genes involved in luciferin metabolism in\u00a0<em>Luciola aquatilis<\/em>\u00a0(Coleoptera: Lampyridae). PeerJ. (2016) e2534.\u00a0<\/li>\n\n\n\n<li>E-kobon, T., K.; Thongararm, P.; Roytrakul, S.; Meesuk, L.;\u00a0<strong>Chumnanpuen, P<\/strong>. (2016). Prediction of anticancer peptides against MCF-7 \u00a0 breast cancer cells from the peptidomes of\u00a0<em>Achatina fulica<\/em>\u00a0mucus fractions.\u00a0<em>Computational and structural biotechnology journal<\/em>.\u00a0<em>14<\/em>, 49-57.\u00a0<\/li>\n\n\n\n<li>Kantawong, F., P. Thaweenan, S. Mungkala, S. Tamang, R. Manaphan, P. Wanachantararak, T. E-kobon,\u00a0<strong>P. Chumnanpuen<\/strong>. (2015). Mucus of\u00a0<em>Achatina fulica<\/em>\u00a0stimulates mineralization and inflammatory response in dental pulp cells.\u00a0<em>Turkish Journal of Biology<\/em>\u00a03: 1-7.<\/li>\n\n\n\n<li>Pewhom, A.,\u00a0<strong>P. Chumnanpuen<\/strong>, I. Muikham, K. Chatchavalvanich and N. Srakaew. (2014). Histomorphological studies of the testis and male genital ducts of Supachai&#8217;s caecilian,\u00a0<em>Ichthyophis supachaii<\/em>\u00a0Taylor, 1960 (Amphibia: Gymnophiona).\u00a0<em>Acta Zoologica<\/em>\u00a097 (1), 76-89.<\/li>\n\n\n\n<li><strong>Chumnanpuen, P<\/strong>., M.A.E.\u00a0Hansen, J.\u00a0Smedsgaard, J.\u00a0Nielsen. (2014). Dynamic metabolic footprinting reveals the key components of metabolic network in yeast\u00a0<em>Saccharomyces cerevisiae<\/em>.\u00a0\u00a0<em>International journal of genomics<\/em>\u00a02014, 894296.<\/li>\n\n\n\n<li><strong>Chumnanpuen, P.<\/strong>, I. Nookaew, J. Nielsen. (2013).\u00a0Integrated analysis, transcriptome-lipidome, reveals the effects of INO-level (<em>INO2 and INO4<\/em>) on lipid metabolism in yeast.\u00a0\u00a0<em>BMC systems biology<\/em>\u00a07 (3), 1-14<\/li>\n\n\n\n<li>Khoomrung, S,\u00a0<strong>P. Chumnanpuen<\/strong>, S. Jansa-Ard, M. St\u00e5hlman, I. Nookaew, J. Bor\u00e9n and J. Nielsen. (2013). Rapid Quantification of Yeast Lipid using Microwave-Assisted Total Lipid Extraction and HPLC-CAD.\u00a0<em>Analytical Chemistry\u00a0<\/em>85(10): 4912-4919.<\/li>\n\n\n\n<li><strong>Chumnanpuen, P.<\/strong>, J. Zhang, I. Nookaew, J. Nielsen. (2012). Integrated analysis of the transcriptome-lipidome reveals the co-influences of inositol-choline and Snf1 in controlling lipid biosynthesis in yeast.\u00a0<em>Mol Genet Genomics<\/em>.\u00a0287(7): 541-54.<\/li>\n\n\n\n<li>Khoomrung, S., S. Jansa-ard, I. Nookaew, J. Nielsen. (2012). Fast and accurate preparation fatty acid methyl esters by microwave-assisted derivatization in yeast\u00a0<em>Saccharomyces cerevisiae<\/em>.\u00a0<em>Applied Microbiology and Biotechnology\u00a0<\/em>94 (6), 1637-1646.<\/li>\n\n\n\n<li><strong>Chumnanpuen P<\/strong>., Brackmann C., Nandy .K.,Chatzipapadopoulos S., Nielsen J., Enejder. A. (2011).\u00a0 Lipid biosynthesis monitored at the single-cell level in\u00a0<em>Saccharomyces cerevisiae<\/em>.\u00a0<em>Biotechnology Journal<\/em>\u00a0<em>7<\/em>. 594-601.<\/li>\n\n\n\n<li>Zhang J., Vaga\u00a0 S.,\u00a0<strong>Chumnanpuen P<\/strong>., Kumar R., Vemuri G.N., Aebersold R., Nielsen J. (2011). Mapping the interaction of Snf1 with TORC1 in\u00a0<em>Saccharomyces cerevisiae<\/em>.\u00a0<em>Molecular systems biology\u00a0<\/em>7 (1), 545.<\/li>\n\n\n\n<li><strong>Chumnanpuen P<\/strong>., Kovitvadhi U., Chatchavalvanich K., Thongpan A., Kovitvadhi S. (2011). Morphological development of glochidia in artificial media through early juvenile of freshwater pearl mussel,\u00a0<em>Hyriopsis (Hyriopsis) bialatus<\/em>\u00a0Simpson, 1900.<em>\u00a0Invertebrate Reproduction &amp; Development\u00a0<\/em>55 (1), 40-52.<\/li>\n\n\n\n<li>Canelas A.B.,\u00a0Harrison N., Fazio A., Zhang J., Pitkanen, J.P., van den Brink J., Bakker B.M., Bogner, L., Bouwman J., Castrillo J.I., Cankorur A.,\u00a0<strong>Chumnanpuen P<\/strong>., Daran-Lapujade P., Dikicioglu D., van Eunen K., Ewald J.C., Heijnen J.J., Kirdar B., Mattila I., Mensonides F.I., Niebel A., Penttila M., Pronk J.T., Reuss M., Salusjarvi\u00a0L., Sauer U., Sherman D., Siemann-Herzberg M., Westerhoff H., de Winde J., Petranovic D., Oliver S.G., Workman C.T., Zamboni N., Nielsen J. (2010). Integrated multilaboratory systems biology reveals differences in protein metabolism between two reference yeast strains.\u00a0<em>Nature Communication.<\/em>\u00a0<em>1<\/em>, 145.\u00a0<\/li>\n<\/ul>\n","protected":false},"featured_media":36762,"parent":0,"template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-36761","ku-personnel","type-ku-personnel","status-publish","has-post-thumbnail","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u0e23\u0e28.\u0e14\u0e23.\u0e1b\u0e23\u0e32\u0e42\u0e21\u0e17\u0e22\u0e4c \u0e0a\u0e33\u0e19\u0e32\u0e0d\u0e1b\u0e37\u0e19 - \u0e20\u0e32\u0e04\u0e27\u0e34\u0e0a\u0e32\u0e2a\u0e31\u0e15\u0e27\u0e27\u0e34\u0e17\u0e22\u0e32 \u0e04\u0e13\u0e30\u0e27\u0e34\u0e17\u0e22\u0e32\u0e28\u0e32\u0e2a\u0e15\u0e23\u0e4c 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