Abstract

Genomics: Using Deep Learning to Accelerate the Identification of Genetic Variants

Identifying genetic variants, interpreting the change (annotation), and determining whether it is pathogenic are critical steps in applying genomics to healthcare. Attendees will implement deep learning methods on genomic data to identify pathogenic variants with high accuracy and speed. They will perform data reduction and train their own models. ....


Speaker: Nicola Rieke
Type:

DLI Instructor-Led Training

Date: Thursday - October 18, 2018 03:30 PM - 05:30 PM
Location: Hall C1
Industry: Software

 

Identifying genetic variants, interpreting the change (annotation), and determining whether it is pathogenic are critical steps in applying genomics to healthcare. Attendees will implement deep learning methods on genomic data to identify pathogenic variants with high accuracy and speed. They will perform data reduction and train their own models. By varying parameters in the model, DANN (Deleterious Annotation of Genetic Variants Using Neural Networks) run on Nvidia's GPC, they will create an ROC to compare with variant annotators from prior scientific publications. Attendees will complete the lab understanding how deep learning improves genomic data analysis using the GPU platform. Prerequisites: None