{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T20:23:06Z","timestamp":1791404586744,"version":"4.3.3"},"reference-count":205,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,11,13]],"date-time":"2024-11-13T00:00:00Z","timestamp":1731456000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biology"],"abstract":"<jats:p>Multiple myeloma is a complex and challenging type of blood cancer that affects plasma cells in the bone marrow. In recent years, the development of advanced research techniques, such as omics approaches\u2014which involve studying large sets of biological data like genes and proteins\u2014and high-throughput sequencing technologies, has allowed researchers to analyze vast amounts of genetic information rapidly and gain new insights into the disease. Additionally, the advent of artificial intelligence tools has accelerated data analysis, enabling more accurate predictions and improved treatment strategies. This review aims to highlight recent research advances in multiple myeloma made possible by these novel techniques and to provide guidance for researchers seeking effective approaches in this field.<\/jats:p>","DOI":"10.3390\/biology13110923","type":"journal-article","created":{"date-parts":[[2024,11,13]],"date-time":"2024-11-13T09:59:11Z","timestamp":1731491951000},"page":"923","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Advancements in Multiple Myeloma Research: High-Throughput Sequencing Technologies, Omics, and the Role of Artificial Intelligence"],"prefix":"10.3390","volume":"13","author":[{"given":"Alejandra","family":"Guti\u00e9rrez-Gonz\u00e1lez","sequence":"first","affiliation":[{"name":"DS-OMICS\u2014Data Science and Omics, AI-Driven Biomedicine Group, Universidad Alfonso X el Sabio, 28619 Villanueva de la Ca\u00f1ada, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Irene","family":"Del Hierro","sequence":"additional","affiliation":[{"name":"DS-OMICS\u2014Data Science and Omics, AI-Driven Biomedicine Group, Universidad Alfonso X el Sabio, 28619 Villanueva de la Ca\u00f1ada, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1457-995X","authenticated-orcid":false,"given":"Ariel Ernesto","family":"Cariaga-Mart\u00ednez","sequence":"additional","affiliation":[{"name":"DS-OMICS\u2014Data Science and Omics, AI-Driven Biomedicine Group, Universidad Alfonso X el Sabio, 28619 Villanueva de la Ca\u00f1ada, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"8","DOI":"10.3322\/caac.21824","article-title":"Cancer Statistics 2024: All Hands on Deck. 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