DrQi’s tutorial talk at UVA-VADC seminar on “Make Deep Learning Interpretable for Sequential Data Analysis in Biomedicine” (Including our work on DeepChrome - AttentiveChrome - GCNChrome - DeepMotif - DeepVHPPI - MotifTransformer)

less than 1 minute read

I gave a tutorial talk at UVA-VADC Seminar Series 2021.

Title: Make Deep Learning Interpretable for Sequential Data Analysis in Biomedicine

Slide PDF


This tutorial includes four of our recent papers:

Tool DeepChrome: deep-learning for predicting gene expression from histone modifications

Tool AttentiveChrome: Attend and Predict: Using Deep Attention Model to Understand Gene Regulation by Selective Attention on Chromatin

Tool: GCNChrome: Graph Convolutional Networks for Epigenetic State Prediction Using Both Sequence and 3D Genome Data

Tool: Transfer Learning for Predicting Virus-Host Protein Interactions for Novel Virus Sequences


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