001024532 001__ 1024532
001024532 005__ 20250203103128.0
001024532 0247_ $$2doi$$a10.3389/fchem.2022.1059593
001024532 0247_ $$2datacite_doi$$a10.34734/FZJ-2024-02219
001024532 0247_ $$2pmid$$a36700074
001024532 0247_ $$2WOS$$aWOS:000921373000001
001024532 037__ $$aFZJ-2024-02219
001024532 082__ $$a540
001024532 1001_ $$0P:(DE-HGF)0$$aOliva, Francesco$$b0
001024532 245__ $$aModelling eNvironment for Isoforms (MoNvIso): A general platform to predict structural determinants of protein isoforms in genetic diseases
001024532 260__ $$aLausanne$$bFrontiers Media$$c2023
001024532 3367_ $$2DRIVER$$aarticle
001024532 3367_ $$2DataCite$$aOutput Types/Journal article
001024532 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1712646353_29216
001024532 3367_ $$2BibTeX$$aARTICLE
001024532 3367_ $$2ORCID$$aJOURNAL_ARTICLE
001024532 3367_ $$00$$2EndNote$$aJournal Article
001024532 520__ $$aThe seamless integration of human disease-related mutation data into proteinstructures is an essential component of any attempt to correctly assess theimpact of the mutation. The key step preliminary to any structural modelling isthe identification of the isoforms onto which mutations should be mapped dueto there being several functionally different protein isoforms from the samegene. To handle large sets of data coming from omics techniques, thischallenging task needs to be automatized. Here we present the MoNvIso(Modelling eNvironment for Isoforms) code, which identifies the most usefulisoform for computational modelling, balancing the coverage of mutations ofinterest and the availability of templates to build a structural model of both thewild-type isoform and the related variants.
001024532 536__ $$0G:(DE-HGF)POF4-5241$$a5241 - Molecular Information Processing in Cellular Systems (POF4-524)$$cPOF4-524$$fPOF IV$$x0
001024532 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
001024532 7001_ $$0P:(DE-HGF)0$$aMusiani, Francesco$$b1
001024532 7001_ $$0P:(DE-Juel1)165199$$aGiorgetti, Alejandro$$b2$$ufzj
001024532 7001_ $$0P:(DE-HGF)0$$aDe Rubeis, Silvia$$b3
001024532 7001_ $$aSorokina, Oksana$$b4
001024532 7001_ $$aArmstrong, Douglas J.$$b5
001024532 7001_ $$0P:(DE-Juel1)145614$$aCarloni, Paolo$$b6$$ufzj
001024532 7001_ $$0P:(DE-HGF)0$$aRuggerone, Paolo$$b7$$eCorresponding author
001024532 773__ $$0PERI:(DE-600)2711776-5$$a10.3389/fchem.2022.1059593$$gVol. 10, p. 1059593$$p1059593$$tFrontiers in Chemistry$$v10$$x2296-2646$$y2023
001024532 8564_ $$uhttps://juser.fz-juelich.de/record/1024532/files/fchem-10-1059593.pdf$$yOpenAccess
001024532 8564_ $$uhttps://juser.fz-juelich.de/record/1024532/files/fchem-10-1059593.gif?subformat=icon$$xicon$$yOpenAccess
001024532 8564_ $$uhttps://juser.fz-juelich.de/record/1024532/files/fchem-10-1059593.jpg?subformat=icon-1440$$xicon-1440$$yOpenAccess
001024532 8564_ $$uhttps://juser.fz-juelich.de/record/1024532/files/fchem-10-1059593.jpg?subformat=icon-180$$xicon-180$$yOpenAccess
001024532 8564_ $$uhttps://juser.fz-juelich.de/record/1024532/files/fchem-10-1059593.jpg?subformat=icon-640$$xicon-640$$yOpenAccess
001024532 909CO $$ooai:juser.fz-juelich.de:1024532$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
001024532 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)165199$$aForschungszentrum Jülich$$b2$$kFZJ
001024532 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)145614$$aForschungszentrum Jülich$$b6$$kFZJ
001024532 9131_ $$0G:(DE-HGF)POF4-524$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5241$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vMolecular and Cellular Information Processing$$x0
001024532 9141_ $$y2024
001024532 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2023-08-19
001024532 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2023-08-19
001024532 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
001024532 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bFRONT CHEM : 2022$$d2023-08-19
001024532 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bFRONT CHEM : 2022$$d2023-08-19
001024532 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2021-05-13T10:38:39Z
001024532 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2021-05-13T10:38:39Z
001024532 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2023-08-19
001024532 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2023-08-19
001024532 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2023-08-19
001024532 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
001024532 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Anonymous peer review$$d2021-05-13T10:38:39Z
001024532 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2023-08-19
001024532 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2023-08-19
001024532 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2023-08-19
001024532 915__ $$0StatID:(DE-HGF)0320$$2StatID$$aDBCoverage$$bPubMed Central$$d2023-08-19
001024532 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2023-08-19
001024532 920__ $$lyes
001024532 9201_ $$0I:(DE-Juel1)IAS-5-20120330$$kIAS-5$$lComputational Biomedicine$$x0
001024532 9201_ $$0I:(DE-Juel1)INM-9-20140121$$kINM-9$$lComputational Biomedicine$$x1
001024532 980__ $$ajournal
001024532 980__ $$aVDB
001024532 980__ $$aUNRESTRICTED
001024532 980__ $$aI:(DE-Juel1)IAS-5-20120330
001024532 980__ $$aI:(DE-Juel1)INM-9-20140121
001024532 9801_ $$aFullTexts