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The Essentials of Multiomics

DC Field Value Language
dc.contributor.author라선영-
dc.date.accessioned2022-08-23T00:19:27Z-
dc.date.available2022-08-23T00:19:27Z-
dc.date.issued2022-04-
dc.identifier.issn1083-7159-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/189371-
dc.description.abstractWithin the last decade, the science of molecular testing has evolved from single gene and single protein analysis to broad molecular profiling as a standard of care, quickly transitioning from research to practice. Terms such as genomics, transcriptomics, proteomics, circulating omics, and artificial intelligence are now commonplace, and this rapid evolution has left us with a significant knowledge gap within the medical community. In this paper, we attempt to bridge that gap and prepare the physician in oncology for multiomics, a group of technologies that have gone from looming on the horizon to become a clinical reality. The era of multiomics is here, and we must prepare ourselves for this exciting new age of cancer medicine.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherAlphaMed Press-
dc.relation.isPartOfONCOLOGIST-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHArtificial Intelligence*-
dc.subject.MESHGenomics-
dc.subject.MESHHumans-
dc.subject.MESHMedical Oncology-
dc.subject.MESHNeoplasms* / genetics-
dc.subject.MESHNeoplasms* / therapy-
dc.subject.MESHProteomics-
dc.titleThe Essentials of Multiomics-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Internal Medicine (내과학교실)-
dc.contributor.googleauthorJohn L Marshall-
dc.contributor.googleauthorBeth N Peshkin-
dc.contributor.googleauthorTakayuki Yoshino-
dc.contributor.googleauthorJakob Vowinckel-
dc.contributor.googleauthorHåvard E Danielsen-
dc.contributor.googleauthorGerry Melino-
dc.contributor.googleauthorIoannis Tsamardinos-
dc.contributor.googleauthorChristian Haudenschild-
dc.contributor.googleauthorDavid J Kerr-
dc.contributor.googleauthorCarlos Sampaio-
dc.contributor.googleauthorSun Young Rha-
dc.contributor.googleauthorKevin T FitzGerald-
dc.contributor.googleauthorEric C Holland-
dc.contributor.googleauthorDavid Gallagher-
dc.contributor.googleauthorJesus Garcia-Foncillas-
dc.contributor.googleauthorHartmut Juhl-
dc.identifier.doi10.1093/oncolo/oyab048-
dc.contributor.localIdA01316-
dc.relation.journalcodeJ02415-
dc.identifier.eissn1549-490X-
dc.identifier.pmid35380712-
dc.subject.keywordartificial intelligence-
dc.subject.keywordcancer-
dc.subject.keyworddigital pathology-
dc.subject.keywordgenomics-
dc.subject.keywordmachine learning-
dc.subject.keywordmultiomics-
dc.subject.keywordproteomics-
dc.subject.keywordtranscriptomics-
dc.contributor.alternativeNameRha, Sun Young-
dc.contributor.affiliatedAuthor라선영-
dc.citation.volume27-
dc.citation.number4-
dc.citation.startPage272-
dc.citation.endPage284-
dc.identifier.bibliographicCitationONCOLOGIST, Vol.27(4) : 272-284, 2022-04-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers

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