000298994 001__ 298994
000298994 005__ 20250302015354.0
000298994 0247_ $$2doi$$a10.1038/s41467-025-57078-0
000298994 0247_ $$2pmid$$apmid:39979307
000298994 0247_ $$2pmc$$apmc:PMC11842776
000298994 0247_ $$2altmetric$$aaltmetric:174350698
000298994 037__ $$aDKFZ-2025-00404
000298994 041__ $$aEnglish
000298994 082__ $$a500
000298994 1001_ $$00000-0003-4439-3136$$aBenfatto, Salvatore$$b0
000298994 245__ $$aExplainable artificial intelligence of DNA methylation-based brain tumor diagnostics.
000298994 260__ $$a[London]$$bSpringer Nature$$c2025
000298994 3367_ $$2DRIVER$$aarticle
000298994 3367_ $$2DataCite$$aOutput Types/Journal article
000298994 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1740473497_18639
000298994 3367_ $$2BibTeX$$aARTICLE
000298994 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000298994 3367_ $$00$$2EndNote$$aJournal Article
000298994 520__ $$aWe have recently developed a machine learning classifier that enables fast, accurate, and affordable classification of brain tumors based on genome-wide DNA methylation profiles that is widely employed in the clinic. Neuro-oncology research would benefit greatly from understanding the underlying artificial intelligence decision process, which currently remains unclear. Here, we describe an interpretable framework to explain the classifier's decisions. We show that functional genomic regions of various sizes are predominantly employed to distinguish between different tumor classes, ranging from enhancers and CpG islands to large-scale heterochromatic domains. We detect a high degree of genomic redundancy, with many genes distinguishing individual tumor classes, explaining the robustness of the classifier and revealing potential targets for further therapeutic investigation. We anticipate that our resource will build up trust in machine learning in clinical settings, foster biomarker discovery and development of compact point-of-care assays, and enable further epigenome research of brain tumors. Our interpretable framework is accessible to the research community via an interactive web application ( https://hovestadtlab.shinyapps.io/shinyMNP/ ).
000298994 536__ $$0G:(DE-HGF)POF4-312$$a312 - Funktionelle und strukturelle Genomforschung (POF4-312)$$cPOF4-312$$fPOF IV$$x0
000298994 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
000298994 650_7 $$2NLM Chemicals$$aBiomarkers, Tumor
000298994 650_2 $$2MeSH$$aDNA Methylation
000298994 650_2 $$2MeSH$$aHumans
000298994 650_2 $$2MeSH$$aBrain Neoplasms: genetics
000298994 650_2 $$2MeSH$$aBrain Neoplasms: diagnosis
000298994 650_2 $$2MeSH$$aArtificial Intelligence
000298994 650_2 $$2MeSH$$aCpG Islands: genetics
000298994 650_2 $$2MeSH$$aMachine Learning
000298994 650_2 $$2MeSH$$aBiomarkers, Tumor: genetics
000298994 7001_ $$0P:(DE-He78)45440b44791309bd4b7dbb4f73333f9b$$aSill, Martin$$b1$$udkfz
000298994 7001_ $$0P:(DE-He78)551bb92841f634070997aa168d818492$$aJones, David$$b2$$udkfz
000298994 7001_ $$0P:(DE-He78)f746aa965c4e1af518b016de3aaff5d9$$aPfister, Stefan$$b3$$udkfz
000298994 7001_ $$0P:(DE-He78)a1f4b408b9155beb2a8f7cba4d04fe88$$aSahm, Felix$$b4$$udkfz
000298994 7001_ $$0P:(DE-He78)a8a10626a848d31e70cfd96a133cc144$$avon Deimling, Andreas$$b5$$udkfz
000298994 7001_ $$0P:(DE-He78)51bf9ae9cb5771b30c483e5597ef606c$$aCapper, David$$b6$$udkfz
000298994 7001_ $$aHovestadt, Volker$$b7
000298994 773__ $$0PERI:(DE-600)2553671-0$$a10.1038/s41467-025-57078-0$$gVol. 16, no. 1, p. 1787$$n1$$p1787$$tNature Communications$$v16$$x2041-1723$$y2025
000298994 909CO $$ooai:inrepo02.dkfz.de:298994$$pVDB
000298994 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)45440b44791309bd4b7dbb4f73333f9b$$aDeutsches Krebsforschungszentrum$$b1$$kDKFZ
000298994 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)551bb92841f634070997aa168d818492$$aDeutsches Krebsforschungszentrum$$b2$$kDKFZ
000298994 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)f746aa965c4e1af518b016de3aaff5d9$$aDeutsches Krebsforschungszentrum$$b3$$kDKFZ
000298994 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)a1f4b408b9155beb2a8f7cba4d04fe88$$aDeutsches Krebsforschungszentrum$$b4$$kDKFZ
000298994 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)a8a10626a848d31e70cfd96a133cc144$$aDeutsches Krebsforschungszentrum$$b5$$kDKFZ
000298994 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)51bf9ae9cb5771b30c483e5597ef606c$$aDeutsches Krebsforschungszentrum$$b6$$kDKFZ
000298994 9131_ $$0G:(DE-HGF)POF4-312$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vFunktionelle und strukturelle Genomforschung$$x0
000298994 9141_ $$y2025
000298994 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bNAT COMMUN : 2022$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2024-01-30T07:48:07Z
000298994 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2024-01-30T07:48:07Z
000298994 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Peer review$$d2024-01-30T07:48:07Z
000298994 915__ $$0LIC:(DE-HGF)CCBYNV$$2V:(DE-HGF)$$aCreative Commons Attribution CC BY (No Version)$$bDOAJ$$d2024-01-30T07:48:07Z
000298994 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)1040$$2StatID$$aDBCoverage$$bZoological Record$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)1060$$2StatID$$aDBCoverage$$bCurrent Contents - Agriculture, Biology and Environmental Sciences$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)9915$$2StatID$$aIF >= 15$$bNAT COMMUN : 2022$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2025-01-02
000298994 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2025-01-02
000298994 9201_ $$0I:(DE-He78)B062-20160331$$kB062$$lB062 Pädiatrische Neuroonkologie$$x0
000298994 9201_ $$0I:(DE-He78)HD01-20160331$$kHD01$$lDKTK HD zentral$$x1
000298994 9201_ $$0I:(DE-He78)B360-20160331$$kB360$$lPädiatrische Gliomforschung$$x2
000298994 9201_ $$0I:(DE-He78)B300-20160331$$kB300$$lKKE Neuropathologie$$x3
000298994 9201_ $$0I:(DE-He78)BE01-20160331$$kBE01$$lDKTK Koordinierungsstelle Berlin$$x4
000298994 980__ $$ajournal
000298994 980__ $$aVDB
000298994 980__ $$aI:(DE-He78)B062-20160331
000298994 980__ $$aI:(DE-He78)HD01-20160331
000298994 980__ $$aI:(DE-He78)B360-20160331
000298994 980__ $$aI:(DE-He78)B300-20160331
000298994 980__ $$aI:(DE-He78)BE01-20160331
000298994 980__ $$aUNRESTRICTED