Article

Metric learning enables synthesis of heterogeneous single-cell modalities

2019-11-08

Abstract excerpt

A complete understanding of biological processes requires synthesizing information across heterogeneous modalities, such as age, disease status, or gene/protein expression. Until recently, single-cell profiling experiments could measure only a single modality, leading to analysis focused on integrating information across separate experiments. However, researchers can now measure multiple modalities simultaneously...

Topics

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

Identifiers and source

Literature Corpus work: 051e15e0-d71b-5218-bc7e-170460f103a8
DOI: 10.1101/834549

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Metric learning enables synthesis of heterogeneous single-cell modalitiesDOI 10.1101/834549Read

Schema: metric learning enables interpretable synthesis of heterogeneous single-cell modalitiesSemantic proximity Read

Dictionary learning for integrative, multimodal, and scalable single-cell analysisSemantic proximity Read

Move BeTween modAlities (MBTA) employs flow matching to predict single cell data modalitiesSemantic proximity Read

Comparing phenotypic manifolds with Kompot: Detecting differential abundance and gene expression at single-cell resolutionSemantic proximity Read

BABEL enables cross-modality translation between multi-omic profiles at single-cell resolutionSemantic proximity Read

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

Scalable querying of human cell atlases via a foundational model reveals commonalities across fibrosis-associated macrophagesSemantic proximity Read

Construction of continuously expandable single-cell atlases through integration of heterogeneous datasets in a generalized cell-embedding spaceSemantic proximity Read

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

A Comprehensive Benchmarking Study on Computational Tools for Cross-omics Label Transfer from Single-cell RNA to ATAC DataSemantic proximity Read

Unify: Learning Cellular Evolution with Universal Multimodal EmbeddingsSemantic proximity Read

scFeatures: Multi-view representations of single-cell and spatial data for disease outcome predictionSemantic proximity Read