2.7k citations · 3.7k across the 9 of their papers we have counts for
10 papers
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling
Romain Lopez, Nataša Tagasovska, Stephen Ra +3
Latent variable models such as the Variational Auto-Encoder (VAE) have become a go-to tool for analyzing biological data, especially in the field of single-cell genomics. One remai…
Large-Scale Differentiable Causal Discovery of Factor Graphs
Romain Lopez, Jan-Christian Hütter, Jonathan K. Pritchard +1
A common theme in causal inference is learning causal relationships between observed variables, also known as causal discovery. This is usually a daunting task, given the large num…
Cell types and ontologies of the Human Cell Atlas
David Osumi-Sutherland, Chuan Xu, Maria Keays +4
Massive single-cell profiling efforts have accelerated our discovery of the cellular composition of the human body, while at the same time raising the need to formalise this new kn…
Inference of cell dynamics on perturbation data using adjoint sensitivity
Weiqi Ji, Bo Yuan, Ciyue Shen +3
Data-driven dynamic models of cell biology can be used to predict cell response to unseen perturbations. Recent work (CellBox) had demonstrated the derivation of interpretable mode…
The necessity and power of random, under-sampled experiments in biology
Brian Cleary, Aviv Regev
A vast array of transformative technologies developed over the past decade has enabled measurement and perturbation at ever increasing scale, yet our understanding of many systems…
SARS-CoV-2 Entry Genes Are Most Highly Expressed in Nasal Goblet and Ciliated Cells within Human Airways
Waradon Sungnak, Ni Huang, Christophe Bécavin +2
The SARS-CoV-2 coronavirus, the etiologic agent responsible for COVID-19 coronavirus disease, is a global threat. To better understand viral tropism, we assessed the RNA expression…