ArticleCell genomics2025
Evaluating methods for the prediction of cell-type-specific enhancers in the mammalian cortex.
Article in Cell genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Article
- A toolkit for modeling cis-regulatory logic of enhancers at large scale.Nature methods · 2026Article
- CREsted: modeling genomic and synthetic cell-type-specific enhancers across tissues and species.Nature methods · 2026Article
- Technical and biological sources of noise confound multiplexed enhancer AAV screening.Nature communications · 2026Article
- Multi-omic profiling of human and mouse dorsal root ganglia enables targeted gene delivery to nociceptors.bioRxiv : the preprint server for biology · 2026Article
- Expanding the fly eye gene regulatory network: From Drosophila to the hoverfly Episyrphus balteatus.PLoS genetics · 2026Article
- The regulatory code of injury-responsive enhancers enables precision cell-state targeting in the CNS.Nature neuroscience · 2026Article
- Evaluating single-cell ATAC-seq atlasing technologies using sequence-to-function modeling.Nature communications · 2026Article
- Human Neocortical Glutamatergic Neurons Revealed Through Multimodal Profiling.bioRxiv : the preprint server for biology · 2026Article
- Cross-species consensus atlas of the primate basal ganglia.bioRxiv : the preprint server for biology · 2025Article
- BayesCNet: Bayesian inference for cell type-specific regulatory networks leveraging cell type hierarchy in single-cell data.bioRxiv : the preprint server for biology · 2025Article
- RNA-programmable cell-type monitoring and manipulation in the human cortex with CellREADR.Cell reports · 2025Article
- A suite of enhancer AAVs and transgenic mouse lines for genetic access to cortical cell types.bioRxiv : the preprint server for biology · 2024Article
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34 authors.
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Abstract
Identifying cell-type-specific enhancers is critical for developing genetic tools to study the mammalian brain. We organized the "Brain Initiative Cell Census Network (BICCN) Challenge: Predicting Functional Cell Type-Specific Enhancers from Cross-Species Multi-Omics" to evaluate machine learning and feature-based methods for nominating enhancer sequences targeting mouse cortical cell types. Methods were assessed using in vivo data from hundreds of adeno-associated virus (AAV)-packaged, retro-orbitally delivered enhancers. Open chromatin was the strongest predictor of functional enhancers, while sequence models improved prediction of non-functional enhancers and identified cell-type-specific transcription factor codes to inform in silico enhancer design. This challenge establishes a benchmark for enhancer prioritization and highlights computational and molecular features critical for identifying functional cortical enhancers, advancing efforts to map and manipulate gene regulation in the mammalian cortex.
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