000088167 001__ 88167
000088167 005__ 20230706131403.0
000088167 0247_ $$2doi$$a10.3390/ijms21031042
000088167 0248_ $$2sideral$$a116235
000088167 037__ $$aART-2020-116235
000088167 041__ $$aeng
000088167 100__ $$0(orcid)0000-0002-4703-6620$$aLatorre-Pellicer, Ana
000088167 245__ $$aEvaluating Face2Gene as a Tool to Identify Cornelia de Lange Syndrome by Facial Phenotypes
000088167 260__ $$c2020
000088167 5060_ $$aAccess copy available to the general public$$fUnrestricted
000088167 5203_ $$aCharacteristic or classic phenotype of Cornelia de Lange syndrome (CdLS) is associated with a recognisable facial pattern. However, the heterogeneity in causal genes and the presence of overlapping syndromes have made it increasingly difficult to diagnose only by clinical features. DeepGestalt technology, and its app Face2Gene, is having a growing impact on the diagnosis and management of genetic diseases by analysing the features of affected individuals. Here, we performed a phenotypic study on a cohort of 49 individuals harbouring causative variants in known CdLS genes in order to evaluate Face2Gene utility and sensitivity in the clinical diagnosis of CdLS. Based on the profile images of patients, a diagnosis of CdLS was within the top five predicted syndromes for 97.9% of our cases and even listed as first prediction for 83.7%. The age of patients did not seem to affect the prediction accuracy, whereas our results indicate a correlation between the clinical score and affected genes. Furthermore, each gene presents a different pattern recognition that may be used to develop new neural networks with the goal of separating different genetic subtypes in CdLS. Overall, we conclude that computer-assisted image analysis based on deep learning could support the clinical diagnosis of CdLS
000088167 536__ $$9info:eu-repo/grantAgreement/ES/DGA/B32-17R$$9info:eu-repo/grantAgreement/ES/FIS/PI19-01860$$9info:eu-repo/grantAgreement/ES/MICINN/RTI2018-094434-B-100$$9info:eu-repo/grantAgreement/ES/MINECO/RTC-2017-6494-1
000088167 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000088167 590__ $$a5.923$$b2020
000088167 591__ $$aBIOCHEMISTRY & MOLECULAR BIOLOGY$$b67 / 296 = 0.226$$c2020$$dQ1$$eT1
000088167 591__ $$aCHEMISTRY, MULTIDISCIPLINARY$$b49 / 178 = 0.275$$c2020$$dQ2$$eT1
000088167 592__ $$a1.455$$b2020
000088167 593__ $$aCatalysis$$c2020$$dQ1
000088167 593__ $$aComputer Science Applications$$c2020$$dQ1
000088167 593__ $$aInorganic Chemistry$$c2020$$dQ1
000088167 593__ $$aSpectroscopy$$c2020$$dQ1
000088167 593__ $$aMolecular Biology$$c2020$$dQ1
000088167 593__ $$aOrganic Chemistry$$c2020$$dQ1
000088167 593__ $$aPhysical and Theoretical Chemistry$$c2020$$dQ1
000088167 593__ $$aMedicine (miscellaneous)$$c2020$$dQ1
000088167 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000088167 700__ $$aAscaso, Ángela
000088167 700__ $$aTrujillano, Laura
000088167 700__ $$aGil-Salvador, Marta
000088167 700__ $$0(orcid)0000-0001-9962-2157$$aArnedo, María$$uUniversidad de Zaragoza
000088167 700__ $$aLucia-Campos, Cristina$$uUniversidad de Zaragoza
000088167 700__ $$aAntoñanzas-Pérez, Rebeca$$uUniversidad de Zaragoza
000088167 700__ $$aMarcos-Alcalde, Iñigo
000088167 700__ $$aParenti, Ilaria
000088167 700__ $$0(orcid)0000-0002-0902-387X$$aBueno-Lozano, Gloria$$uUniversidad de Zaragoza
000088167 700__ $$aMusio, Antonio
000088167 700__ $$0(orcid)0000-0003-0170-7326$$aPuisac, Beatriz$$uUniversidad de Zaragoza
000088167 700__ $$aKaiser, Frank J.
000088167 700__ $$0(orcid)0000-0002-5732-2209$$aRamos, Feliciano J.$$uUniversidad de Zaragoza
000088167 700__ $$aGómez-Puertas, Paulino
000088167 700__ $$0(orcid)0000-0003-3203-6254$$aPié, Juan$$uUniversidad de Zaragoza
000088167 7102_ $$11012$$2410$$aUniversidad de Zaragoza$$bDpto. Farmac.Fisiol.y Med.L.F.$$cÁrea Fisiología
000088167 7102_ $$11012$$2X$$aUniversidad de Zaragoza$$bDpto. Farmac.Fisiol.y Med.L.F.$$cProy. investigación DUA
000088167 7102_ $$11011$$2670$$aUniversidad de Zaragoza$$bDpto. Microb.Ped.Radio.Sal.Pú.$$cÁrea Pediatría
000088167 773__ $$g21, 3 (2020), 1042 [12 pp.]$$pInt. j. mol. sci.$$tInternational Journal of Molecular Sciences$$x1661-6596
000088167 8564_ $$s3958886$$uhttps://zaguan.unizar.es/record/88167/files/texto_completo.pdf$$yVersión publicada
000088167 8564_ $$s469414$$uhttps://zaguan.unizar.es/record/88167/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000088167 909CO $$ooai:zaguan.unizar.es:88167$$particulos$$pdriver
000088167 951__ $$a2023-07-06-12:20:35
000088167 980__ $$aARTICLE