Hail-Powered Science

The following is an incomplete list of scientific work enabled by Hail. We welcome you to add additional examples by editing this page directly, after which we will review the pull request to confirm the addition is valid. Please adhere to the existing formatting conventions.

In addition to software development, the Hail team engages in theoretical, algorithmic, and empirical research inspired by scientific collaboration. Examples include Loss landscapes of regularized linear autoencoders, Secure multi-party linear regression at plaintext speed, and A synthetic-diploid benchmark for accurate variant-calling evaluation.

Last updated on February 3rd, 2020 at 11:00 AM EST