📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Machine learning of stem cell identities from single-cell expression data via regulatory network archetypes (2017)

First Author: Stumpf P

Attributed to: Dissecting the molecular basis of cell-cell variability in mouse embryonic stem cell populations using systems approaches funded by BBSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1101/208470

Publication URI: http://dx.doi.org/10.1101/208470

Type: Preprint