Computational Tools for Splicing Defect Prediction in Breast/Ovarian Cancer Genes: How Efficient Are They at Predicting RNA Alterations?

In silico tools for splicing defect prediction have a key role to assess the impact of variants of uncertain significance. Our aim was to evaluate the performance of a set of commonly used splicing in silico tools comparing the predictions against RNA in vitro results. This was done for natural spli...

Πλήρης περιγραφή

Αποθηκεύτηκε σε:
Λεπτομέρειες βιβλιογραφικής εγγραφής
Τόπος έκδοσης:Front Genet
Κύριοι συγγραφείς: Moles-Fernández, Alejandro, Duran-Lozano, Laura, Montalban, Gemma, Bonache, Sandra, López-Perolio, Irene, Menéndez, Mireia, Santamariña, Marta, Behar, Raquel, Blanco, Ana, Carrasco, Estela, López-Fernández, Adrià, Stjepanovic, Neda, Balmaña, Judith, Capellá, Gabriel, Pineda, Marta, Vega, Ana, Lázaro, Conxi, de la Hoya, Miguel, Diez, Orland, Gutiérrez-Enríquez, Sara
Μορφή: Artigo
Γλώσσα:Inglês
Έκδοση: Frontiers Media S.A. 2018
Θέματα:
Genetics
Διαθέσιμο Online:https://ncbi.nlm.nih.gov/pmc/articles/PMC6134256/
https://ncbi.nlm.nih.gov/pubmed/30233647
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fgene.2018.00366
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