[HTML][HTML] Machine learning for perturbational single-cell omics

Y Ji, M Lotfollahi, FA Wolf, FJ Theis - Cell Systems, 2021 - cell.com
Cell biology is fundamentally limited in its ability to collect complete data on cellular
phenotypes and the wide range of responses to perturbation. Areas such as computer vision …

Open problems in human trait genetics

N Brandes, O Weissbrod, M Linial - Genome Biology, 2022 - Springer
Genetic studies of human traits have revolutionized our understanding of the variation
between individuals, and yet, the genetics of most traits is still poorly understood. In this …

Linking genome variants to disease: scalable approaches to test the functional impact of human mutations

GM Findlay - Human molecular genetics, 2021 - academic.oup.com
The application of genomics to medicine has accelerated the discovery of mutations
underlying disease and has enhanced our knowledge of the molecular underpinnings of …

Cell Painting predicts impact of lung cancer variants

JC Caicedo, J Arevalo, F Piccioni… - Molecular biology of …, 2022 - Am Soc Cell Biol
Most variants in most genes across most organisms have an unknown impact on the
function of the corresponding gene. This gap in knowledge is especially acute in cancer …

Perturbnet predicts single-cell responses to unseen chemical and genetic perturbations

H Yu, JD Welch - BioRxiv, 2022 - biorxiv.org
Small molecule treatment and gene knockout or overexpression induce complex changes in
the molecular states of cells, and the space of possible perturbations is too large to measure …

Identifying disease-critical cell types and cellular processes across the human body by integration of single-cell profiles and human genetics

KA Jagadeesh, KK Dey, DT Montoro, R Mohan… - bioRxiv, 2021 - biorxiv.org
Genome-wide association studies (GWAS) provide a powerful means to identify loci and
genes contributing to disease, but in many cases the related cell types/states through which …

[HTML][HTML] High-performance single-cell gene regulatory network inference at scale: the Inferelator 3.0

CS Gibbs, CA Jackson, GA Saldi, A Tjärnberg… - …, 2022 - ncbi.nlm.nih.gov
Results In this work, we present the Inferelator 3.0, which has been significantly updated to
integrate data from distinct cell types to learn context-specific regulatory networks and …

High-performance single-cell gene regulatory network inference at scale: the Inferelator 3.0

C Skok Gibbs, CA Jackson, GA Saldi… - …, 2022 - academic.oup.com
Motivation Gene regulatory networks define regulatory relationships between transcription
factors and target genes within a biological system, and reconstructing them is essential for …

[HTML][HTML] Single-cell toolkits opening a new era for cell engineering

S Lee, J Kim, JE Park - Molecules and cells, 2021 - Elsevier
Since the introduction of RNA sequencing (RNA-seq) as a high-throughput mRNA
expression analysis tool, this procedure has been increasingly implemented to identify cell …

[HTML][HTML] Discovering chromatin dysregulation induced by protein-coding perturbations at scale

M Frenkel, MLA Hujoel, Z Morris, S Raman - bioRxiv, 2023 - ncbi.nlm.nih.gov
Although population-scale databases have expanded to millions of protein-coding variants,
insight into variant mechanisms has not kept pace. We present PROD-ATAC, a high …