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Article

Phenotype prediction from single-cell RNA-seq data using attention-based neural networks.

Bioinformatics (Oxford, England) - 1 Feb 2024

Mao Yuzhen, Lin Yen-Yi, Wong Nelson K Y, Volik Stanislav, Sar Funda, Collins Colin, Ester Martin

Abstract excerpt

MOTIVATION: A patient's disease phenotype can be driven and determined by specific groups of cells whose marker genes are either unknown or can only be detected at late-stage using conventional bulk assays such as RNA-Seq technology. Recent advances in single-cell RNA sequencing (scRNA-seq) enable gene expression profiling in cell-level resolution, and therefore have the potential to identify those cells driving...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 38390963
DOI: 10.1093/bioinformatics/btae067
PMCID: PMC10902676

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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