JHU Deep Learning in Genomics Journal Club
When Genomics Sequences Meet Deep Learning

Jake Galvin - "Predicting expression-altering promoter mutations with deep learning" (Jaganathan et al.)

Overview

Paper Information

  • Title: Predicting expression-altering promoter mutations with deep learning
  • Authors: Kishore Jaganathan, Nicole Ersaro, Gherman Novakovsky, Yuchuan Wang, Terena James, Jeremy Schwartzentruber, Petko Fiziev, Irfahan Kassam, Fan Cao, Johann Hawe, Henry Cavanagh, Ashley Lim, Grace Png, Jeremy McRae, Abhimanyu Banerjee, Arvind Kumar, Jacob Ulirsch, Yan Zhang, Francois Aguet, Pierrick Wainschtein, Laksshman Sundaram, Adriana Salcedo, Sofia Kyriazopoulou Panagiotopoulou, Delasa Aghamirzaie, Evin Padhi, Ziming Weng, Shan Dong, Damian Smedley, Mark Caulfield, Anne O’Donnell-Luria, Heidi L. Rehm, Stephan J. Sanders, Anshul Kundaje, Stephen B. Montgomery, Mark T. Ross, and Kyle Kai-How Farh
  • Journal: Science Vol. 389 Issue 6760
  • DOI & Link: https://www.science.org/doi/10.1126/science.ads7373

Slides

Below are the slides for this talk, embedded directly from Google Drive:

Slides

Contact

For questions or further discussion, please reach out to genomicdeeplearning@cs.jhu.edu