{"id":482,"date":"2023-06-29T11:41:02","date_gmt":"2023-06-29T09:41:02","guid":{"rendered":"https:\/\/www.iemest.eu\/life-safety-and-security\/2023\/06\/29\/a-six-steps-trip-into-molecular-genetic-implications-of-alzheimer-perusinis-disease-copy\/"},"modified":"2023-07-03T16:47:09","modified_gmt":"2023-07-03T14:47:09","slug":"the-impact-of-artificial-intelligence-on-omics-sciences","status":"publish","type":"post","link":"https:\/\/www.iemest.eu\/life-safety-and-security\/2023\/06\/29\/the-impact-of-artificial-intelligence-on-omics-sciences\/","title":{"rendered":"The impact of artificial intelligence on omics sciences"},"content":{"rendered":"\r\n<p>Luigi Donato,\u00a0Domenico Mord\u00e0, Simona Alibrandi, Concetta Scimone, Alessandra Costa, Fabiana Nicita, Rosalia D\u2019Angelo, Antonina Sidoti<\/p>\r\n\r\n\r\n\r\n<p><strong>Summary<\/strong><\/p>\r\n\r\n\r\n\r\n<p>Artificial Intelligence (AI) and Omics Sciences have the potential to revolutionize healthcare by transforming our understanding of diseases and enabling personalized treatments. Omics Sciences focuses on studying individual-specific biological molecules, generating vast amounts of data that present computational challenges. AI techniques, such as machine learning and deep learning, offer promising solutions to process and interpret this data, improving accuracy in predicting protein functions, developing diagnostics, and identifying therapeutic targets. The integration of AI and Omics Sciences has the power to shift healthcare from reactive to proactive disease prevention and management. By analyzing complex Omics data, AI can unlock new insights, leading to more efficient drug discovery and the identification of biomarkers for early disease detection or predicting treatment response. Personalized medicine stands to benefit greatly from the combination of AI and Omics Sciences. Clinicians can leverage AI algorithms to analyze an individual&#8217;s unique biological data and develop tailored treatment plans. The success of this approach has already been demonstrated in cancer treatment, where genomic analysis helps identify mutations driving tumor growth. In summary, the integration of AI and Omics Sciences offers exciting possibilities for improving healthcare outcomes. Through proactive disease prevention, personalized medicine, and more accurate diagnostics and treatments, these technologies have the potential to transform the field. As AI continues to advance hand in hand with Omics Sciences, we can anticipate significant breakthroughs in understanding diseases and developing targeted therapies.<\/p>\r\n\r\n\r\n\r\n<p><a href=\"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-content\/uploads\/2023\/07\/the-impact-of-artificial-intelligence-on-mics-sciences.pdf\">View article<\/a><\/p>\r\n\r\n\r\n\r\n<p><strong>References<\/strong><\/p>\r\n\r\n\r\n\r\n<p>1.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Ramesh, A.N., C. Kambhampati, J.R. Monson, and P.J. Drew. (2004). Artificial intelligence in medicine. Ann R Coll Surg Engl, 86(5), 334-8.<\/p>\r\n\r\n\r\n\r\n<p>2.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Mintz, Y. and R. Brodie. (2019). Introduction to artificial intelligence in medicine. Minim Invasive Ther Allied Technol, 28(2), 73-81.<\/p>\r\n\r\n\r\n\r\n<p>3.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Manzoni, C., D.A. Kia, J. Vandrovcova, J. Hardy, N.W. Wood, P.A. Lewis, and R. Ferrari. (2018). Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences. Brief Bioinform, 19(2), 286-302.<\/p>\r\n\r\n\r\n\r\n<p>4.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Donato, L., C. Scimone, S. Alibrandi, E.M. Abdalla, K.M. Nabil, R. D&#8217;Angelo, and A. Sidoti. (2020). New Omics-Derived Perspectives on Retinal Dystrophies: Could Ion Channels-Encoding or Related Genes Act as Modifier of Pathological Phenotype? Int J Mol Sci, 22(1).<\/p>\r\n\r\n\r\n\r\n<p>5.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Donato, L., C. Scimone, S. Alibrandi, A. Pitruzzella, F. Scalia, R. D&#8217;Angelo, and A. Sidoti. (2020). Possible A2E Mutagenic Effects on RPE Mitochondrial DNA from Innovative RNA-Seq Bioinformatics Pipeline. Antioxidants (Basel), 9(11).<\/p>\r\n\r\n\r\n\r\n<p>6.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Donato, L., C. Scimone, S. Alibrandi, C. Rinaldi, A. Sidoti, and R. D&#8217;Angelo. (2020). Transcriptome Analyses of lncRNAs in A2E-Stressed Retinal Epithelial Cells Unveil Advanced Links between Metabolic Impairments Related to Oxidative Stress and Retinitis Pigmentosa. Antioxidants (Basel), 9(4).<\/p>\r\n\r\n\r\n\r\n<p>7.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Wu, Y., Y. Cheng, X. Wang, J. Fan, and Q. Gao. (2022). Spatial omics: Navigating to the golden era of cancer research. Clin Transl Med, 12(1), e696.<\/p>\r\n\r\n\r\n\r\n<p>8.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Wang, X.Y., H.Z. Qu, and X.D. Fang. (2021). Omics big data and medical artificial intelligence. Yi Chuan, 43(10), 930-937.<\/p>\r\n\r\n\r\n\r\n<p>9.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Williams, C.G., H.J. Lee, T. Asatsuma, R. Vento-Tormo, and A. Haque. (2022). An introduction to spatial transcriptomics for biomedical research. Genome Med, 14(1), 68.<\/p>\r\n\r\n\r\n\r\n<p>10.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Wang, F. and A. Preininger. (2019). AI in Health: State of the Art, Challenges, and Future Directions. Yearb Med Inform, 28(1), 16-26.<\/p>\r\n\r\n\r\n\r\n<p>11.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Calamuneri, A., L. Donato, C. Scimone, A. Costa, R. D\u2019Angelo, and A. Sidoti. (2017). On Machine Learning in Biomedicine. Life Safety And Security.<\/p>\r\n\r\n\r\n\r\n<p>12.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Hoffman, N.J. (2017). Omics and Exercise: Global Approaches for Mapping Exercise Biological Networks. Cold Spring Harb Perspect Med, 7(10).<\/p>\r\n\r\n\r\n\r\n<p>13.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Forshed, J. (2017). Experimental Design in Clinical &#8216;Omics Biomarker Discovery. J Proteome Res, 16(11), 3954-3960.<\/p>\r\n\r\n\r\n\r\n<p>14.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Lin, B., Y. Ma, and S. Wu. (2022). Multi-Omics and Artificial Intelligence-Guided Data Integration in Chronic Liver Disease: Prospects and Challenges for Precision Medicine. OMICS, 26(8), 415-421.<\/p>\r\n\r\n\r\n\r\n<p>15.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Shen, Y., S. Zhang, J. Zhou, and J. Chen. (2017). Cohort Research in &#8220;Omics&#8221; and Preventive Medicine. Adv Exp Med Biol, 1005, 193-220.<\/p>\r\n\r\n\r\n\r\n<p>16.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Hartl, D., V. de Luca, A. Kostikova, J. Laramie, S. Kennedy, E. Ferrero, R. Siegel, M. Fink, S. Ahmed, J. Millholland, A. Schuhmacher, M. Hinder, L. Piali, and A. Roth. (2021). Translational precision medicine: an industry perspective. J Transl Med, 19(1), 245.<\/p>\r\n\r\n\r\n\r\n<p>17.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Chaussabel,D. and D.Rinchai.(2018).Using &#8216;collective omics data&#8217; for biomedical research training. Immunology, 155(1), 18-23.<\/p>\r\n\r\n\r\n\r\n<p>18.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Gomez-Cabrero, D., I. Abugessaisa, D. Maier, A. Teschendorff, M. Merkenschlager, A. Gisel, E. Ballestar, E. Bongcam-Rudloff, A. Conesa, and J. Tegner. (2014). Data integration in the era of omics: current and future challenges. BMC Syst Biol, 8 Suppl 2(Suppl 2), I1.<\/p>\r\n\r\n\r\n\r\n<p>19.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Gupta, R., D. Srivastava, M. Sahu, S. Tiwari, R.K. Ambasta, and P. Kumar. (2021). Artificial intelligence to deep learning: machine intelligence approach for drug discovery. Mol Divers, 25(3), 1315-1360.<\/p>\r\n\r\n\r\n\r\n<p>20.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Yu, K.H., A.L. Beam, and I.S. Kohane. (2018). Artificial intelligence in healthcare. Nat Biomed Eng, 2(10), 719-731.<\/p>\r\n\r\n\r\n\r\n<p>21.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Nensa, F., A. Demircioglu, and C. Rischpler. (2019). Artificial Intelligence in Nuclear Medicine. J Nucl Med, 60(Suppl 2), 29S-37S.<\/p>\r\n\r\n\r\n\r\n<p>22.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Chen, M. and M. Decary. (2020). Artificial intelligence in healthcare: An essential guide for health leaders. Healthc Manage Forum, 33(1), 10-18.<\/p>\r\n\r\n\r\n\r\n<p>23.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Keskinbora, K. and F. Guven. (2020). Artificial Intelligence and Ophthalmology. Turk J Ophthalmol, 50(1), 37-43.<\/p>\r\n\r\n\r\n\r\n<p>24.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Keskinbora, K.H. (2019). Medical ethics considerations on artificial intelligence. J Clin Neurosci, 64, 277-282.<\/p>\r\n\r\n\r\n\r\n<p>25.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Jimenez-Luna, J., F. Grisoni, N. Weskamp, and G. Schneider. (2021). Artificial intelligence in drug discovery: recent advances and future perspectives. Expert Opin Drug Discov, 16(9), 949-959.<\/p>\r\n\r\n\r\n\r\n<p>26.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Haug, C.J. and J.M. Drazen. (2023). Artificial Intelligence and Machine Learning in Clinical Medicine, 2023. N Engl J Med, 388(13), 1201-1208.<\/p>\r\n\r\n\r\n\r\n<p>27.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Howard, J. (2019). Artificial intelligence: Implications for the future of work. Am J Ind Med, 62(11), 917-926.<\/p>\r\n\r\n\r\n\r\n<p>28.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Liyanage, H., S.T. Liaw, J. Jonnagaddala, R. Schreiber, C. Kuziemsky, A.L. Terry, and S. de Lusignan. (2019). Artificial Intelligence in Primary Health Care: Perceptions, Issues, and Challenges. Yearb Med Inform, 28(1), 41-46.<\/p>\r\n","protected":false},"excerpt":{"rendered":"<p>Luigi Donato,\u00a0Domenico Mord\u00e0, Simona Alibrandi, Concetta Scimone, Alessandra Costa, Fabiana Nicita, Rosalia D\u2019Angelo, Antonina Sidoti Summary Artificial Intelligence (AI) and Omics Sciences have the potential<\/p>\n","protected":false},"author":1,"featured_media":450,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5,3],"tags":[],"class_list":["post-482","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-minireview","category-review"],"_links":{"self":[{"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/posts\/482","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/comments?post=482"}],"version-history":[{"count":5,"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/posts\/482\/revisions"}],"predecessor-version":[{"id":509,"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/posts\/482\/revisions\/509"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/media\/450"}],"wp:attachment":[{"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/media?parent=482"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/categories?post=482"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.iemest.eu\/life-safety-and-security\/wp-json\/wp\/v2\/tags?post=482"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}