Article

Biologically informed deep learning to infer gene program activity in single cells

2022-02-07

Abstract excerpt

The increasing availability of large-scale single-cell datasets has enabled the detailed description of cell states across multiple biological conditions and perturbations. In parallel, recent advances in unsupervised machine learning, particularly in transfer learning, have enabled fast and scalable mapping of these new single-cell datasets onto reference atlases. The resulting large-scale machine learning models...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: df2de260-b686-5864-98ae-4d859c3a1cb3
DOI: 10.1101/2022.02.05.479217

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Biologically informed deep learning to infer gene program activity in single cellsDOI 10.1101/2022.02.05.479217Read

Identification of cell types, states and programs by learning gene set representationsSemantic proximity Read

Exploring phenotype-related single-cells through attention-enhanced representation learningSemantic proximity Read

scEMB: Learning context representation of genes based on large-scale single-cell transcriptomicsSemantic proximity Read

Enhancement of Network Architecture Alignment in Comparative Single-Cell StudiesSemantic proximity Read

GeneCompass: Deciphering Universal Gene Regulatory Mechanisms with Knowledge-Informed Cross-Species Foundation ModelSemantic proximity Read

DiSCERN - Deep Single Cell Expression ReconstructioN for improved cell clustering and cell subtype and state detectionSemantic proximity Read

Directing cellular transitions on gene graph-enhanced cell state manifoldSemantic proximity Read

CAPTAIN: A multimodal foundation model pretrained on co-assayed single-cell RNA and proteinSemantic proximity Read

Knowledge-primed neural networks enable biologically interpretable deep learning on single-cell sequencing dataSemantic proximity Read

RegFormer: A Single-Cell Foundation Model Powered by Gene Regulatory HierarchiesSemantic proximity Read

Decoding cell identity with multi-scale explainable deep learningSemantic proximity Read

Parameter-free representations outperform single-cell foundation models on downstream benchmarksSemantic proximity Read