MET Exon 14 Skipping: A Case Study for the Detection of Genetic Variants in Cancer Driver Genes by Deep Learning.
Vladimir NosiAlessandrì LucaMelissa MilanMaddalena ArigoniSilvia BenvenutiDavide CacchiarelliMarcella CesanaSara RiccardoLucio Di FilippoFrancesca CorderoMarco BeccutiPaolo M ComoglioRaffaele Adolfo CalogeroPublished in: International journal of molecular sciences (2021)
Taken together, our results indicate that neural networks can be an effective tool to provide a quick classification of pathological transcription events, and sparsely connected autoencoders could represent the basis for the development of an effective discovery tool.
Keyphrases
- deep learning
- neural network
- papillary thyroid
- machine learning
- artificial intelligence
- convolutional neural network
- small molecule
- squamous cell
- genome wide
- loop mediated isothermal amplification
- real time pcr
- gene expression
- dna methylation
- young adults
- childhood cancer
- genome wide identification
- bioinformatics analysis
- genome wide analysis