Year: 2021
Type: article
Abstract: Recent advances in sequencing and barcoding technologies have enabled researchers to simultaneously profile gene expression, chromatin accessibility, and/or protein levels in single cells. However, these multiomic techniques often pose technical and financial barriers that limit their practicality. Kevin Wu and colleagues recently developed BABEL, a deep learning algorithm that can effectively translate between transcriptomic and chromatin profiles in single cells, thereby enabling researchers to perform multiomic analyses from an individual dataset.
Source: Communications Biology
Author: George Andrew S. Inglis
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,290
OpenAlex ID: W3163625698