Selected article for: "large scale sequencing and scale sequencing"
Author: Del Giudice, Marco; Peirone, Serena; Perrone, Sarah; Priante, Francesca; Varese, Fabiola; Tirtei, Elisa; Fagioli, Franca; Cereda, Matteo
Title: Artificial Intelligence in Bulk and Single-Cell RNA-Sequencing Data to Foster Precision Oncology
  • Cord-id: 10l606u5
  • Document date: 2021_4_27
    • ID: 10l606u5
    Snippet: Artificial intelligence, or the discipline of developing computational algorithms able to perform tasks that requires human intelligence, offers the opportunity to improve our idea and delivery of precision medicine. Here, we provide an overview of artificial intelligence approaches for the analysis of large-scale RNA-sequencing datasets in cancer. We present the major solutions to disentangle inter- and intra-tumor heterogeneity of transcriptome profiles for an effective improvement of patient
    Document: Artificial intelligence, or the discipline of developing computational algorithms able to perform tasks that requires human intelligence, offers the opportunity to improve our idea and delivery of precision medicine. Here, we provide an overview of artificial intelligence approaches for the analysis of large-scale RNA-sequencing datasets in cancer. We present the major solutions to disentangle inter- and intra-tumor heterogeneity of transcriptome profiles for an effective improvement of patient management. We outline the contributions of learning algorithms to the needs of cancer genomics, from identifying rare cancer subtypes to personalizing therapeutic treatments.

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