Johnny Israeli

TL;DR: It is found that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art.

TL;DR: 3D model of breast cancer shows that a stiff extracellular matrix promotes a tumorigenic phenotype through broad changes in chromatin accessibility and in the activity of histone deacetylases and the transcription factor Sp1, and reveals that chromatin state is a critical mediator of mechanotransduction.

TL;DR: It is argued here that it is a quirk of history that both MRT and gene editing have come to the forefront of public attention at roughly the same time and to best protect citizens from harm, limited regulatory pathways that can be monitored and carefully delineated are preferable to shadowy practices and a potential regulatory race to the bottom.

TL;DR: This work examines applications of deep learning to a variety of biomedical problems -- patient classification, fundamental biological processes, and treatment of patients -- to predict whether deep learning will transform these tasks or if the biomedical sphere poses unique challenges.

TL;DR: Kipoi, a collaborative initiative to define standards and to foster reuse of trained models in genomics, is presented, providing a unified framework to archive, share, access, use, and build on models developed by the community.