{"id":5209,"date":"2025-12-22T09:34:25","date_gmt":"2025-12-22T02:34:25","guid":{"rendered":"https:\/\/www2.si.mahidol.ac.th\/department\/biochemistry\/?p=5209"},"modified":"2026-03-30T15:03:23","modified_gmt":"2026-03-30T08:03:23","slug":"deep-learning-facilitates-multi-data-type-analysis-and-predictive-biomarker-discovery-in-cancer-precision-medicine","status":"publish","type":"post","link":"https:\/\/www2.si.mahidol.ac.th\/department\/biochemistry\/en\/deep-learning-facilitates-multi-data-type-analysis-and-predictive-biomarker-discovery-in-cancer-precision-medicine\/","title":{"rendered":"Deep learning facilitates multi-data type analysis and predictive biomarker discovery in cancer precision medicine"},"content":{"rendered":"\t<div class=\"img has-hover x md-x lg-x y md-y lg-y\" id=\"image_1266740197\">\n\t\t\t\t\t\t\t\t<div class=\"img-inner dark\" >\n\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"719\" height=\"295\" src=\"https:\/\/www2.si.mahidol.ac.th\/department\/biochemistry\/wp-content\/uploads\/2025\/12\/ga1-5.jpg\" class=\"attachment-large size-large\" alt=\"\" \/>\t\t\t\t\t\t\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\n<style>\n#image_1266740197 {\n  width: 100%;\n}\n<\/style>\n\t<\/div>\n\t\n<p>Vivek Bhakta Mathema, Partho Sen, Santosh Lamichhane, Matej Ore\u0161i\u010d, <strong>Sakda Khoomrung<\/strong><\/p>\n<h2 class=\"title\">Abstract<\/h2>\n<div id=\"eng-abstract\" class=\"abstract-content selected\">\n<div class=\"title\">\n<p>Cancer progression is linked to gene-environment interactions that alter cellular homeostasis. The use of biomarkers as early indicators of disease manifestation and progression can substantially improve diagnosis and treatment. Large omics datasets generated by high-throughput profiling technologies, such as microarrays, RNA sequencing, whole-genome shotgun sequencing, nuclear magnetic resonance, and mass spectrometry, have enabled data-driven biomarker discoveries. The identification of differentially expressed traits as molecular markers has traditionally relied on statistical techniques that are often limited to linear parametric modeling. The heterogeneity, epigenetic changes, and high degree of polymorphism observed in oncogenes demand biomarker-assisted personalized medication schemes. Deep learning (DL), a major subunit of machine learning (ML), has been increasingly utilized in recent years to investigate various diseases. The combination of ML\/DL approaches for performance optimization across multi-omics datasets produces robust ensemble-learning prediction models, which are becoming useful in precision medicine. This review focuses on the recent development of ML\/DL methods to provide integrative solutions in discovering cancer-related biomarkers, and their utilization in precision medicine.<\/p>\n<p><a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/36817954\/\">https:\/\/pubmed.ncbi.nlm.nih.gov\/36817954\/<\/a><\/p>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Vivek Bhakta Mathema, Partho Sen, Santosh Lamichhane, Matej Ore\u0161i\u010d, Sakda Khoomrung Abstract Cancer progression is linked to gene-environment interactions that alter cellular homeostasis. The use of biomarkers as early indicators of disease manifestation and progression can substantially improve diagnosis and treatment. Large omics datasets generated by high-throughput profiling technologies, such as microarrays, RNA sequencing, whole-genome [&#8230;]\n","protected":false},"author":6,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[18],"tags":[],"class_list":["post-5209","post","type-post","status-publish","format-standard","hentry","category-research-innovation-en"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Deep learning facilitates multi-data type analysis and predictive biomarker discovery in cancer precision medicine - \u0e20\u0e32\u0e04\u0e27\u0e34\u0e0a\u0e32\u0e0a\u0e35\u0e27\u0e40\u0e04\u0e21\u0e35 \u0e04\u0e13\u0e30\u0e41\u0e1e\u0e17\u0e22\u0e28\u0e32\u0e2a\u0e15\u0e23\u0e4c\u0e28\u0e34\u0e23\u0e34\u0e23\u0e32\u0e0a\u0e1e\u0e22\u0e32\u0e1a\u0e32\u0e25 \u0e21\u0e2b\u0e32\u0e27\u0e34\u0e17\u0e22\u0e32\u0e25\u0e31\u0e22\u0e21\u0e2b\u0e34\u0e14\u0e25<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www2.si.mahidol.ac.th\/department\/biochemistry\/en\/deep-learning-facilitates-multi-data-type-analysis-and-predictive-biomarker-discovery-in-cancer-precision-medicine\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Deep learning facilitates multi-data type analysis and predictive biomarker discovery in cancer precision medicine - \u0e20\u0e32\u0e04\u0e27\u0e34\u0e0a\u0e32\u0e0a\u0e35\u0e27\u0e40\u0e04\u0e21\u0e35 \u0e04\u0e13\u0e30\u0e41\u0e1e\u0e17\u0e22\u0e28\u0e32\u0e2a\u0e15\u0e23\u0e4c\u0e28\u0e34\u0e23\u0e34\u0e23\u0e32\u0e0a\u0e1e\u0e22\u0e32\u0e1a\u0e32\u0e25 \u0e21\u0e2b\u0e32\u0e27\u0e34\u0e17\u0e22\u0e32\u0e25\u0e31\u0e22\u0e21\u0e2b\u0e34\u0e14\u0e25\" \/>\n<meta property=\"og:description\" content=\"Vivek Bhakta Mathema, Partho Sen, Santosh Lamichhane, Matej Ore\u0161i\u010d, Sakda Khoomrung Abstract Cancer progression is linked to gene-environment interactions that alter cellular homeostasis. The use of biomarkers as early indicators of disease manifestation and progression can substantially improve diagnosis and treatment. 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