ReviewBiophysical reviews2024
Progress in single-cell multimodal sequencing and multi-omics data integration.
Review in Biophysical reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed, 31 citations in OpenAlex.
- DeCTCF: Decoding CTCF binding sequences by leveraging predicted epigenomic features.PLoS computational biology · 2026Article
- The dual-enhanced graph learning framework DePass allows paired data integration in single-cell and spatial multiomics.Nature cell biology · 2026Article
- Decoding the cancer microbiome: multi-omics, AI, and translational opportunities.Genome biology · 2026Review
- Topology-guided dual-masked contrastive learning for weakly supervised cell-type annotation in single-cell multi-omics.Briefings in bioinformatics · 2026Article
- Explainable graph learning for multimodal single-cell data integration.BMC bioinformatics · 2026Article
- ALKBH5-Mediated ITGB1 m6A Modification in Ovarian Cancer Progression and Immune Evasion.NPJ precision oncology · 2025Article
- Multi-omics integration and batch correction using a modality-agnostic deep learning framework.bioRxiv : the preprint server for biology · 2025Article
- Single-cell sequencing in diabetic retinopathy: progress and prospects.Journal of translational medicine · 2025Review
- Acetylation-Mediated Epigenetic Consequences for Biological Control and Cancer.Results and problems in cell differentiation · 2025Review
- Navigating Cancer Complexity: Integrative Multi-Omics Methodologies for Clinical Insights.Clinical Medicine Insights. Oncology · 2025Review
- The Dual Role of the TRAIL-DR5 Signaling Axis in Cardiovascular Disease: From Molecular Mechanisms to Targeted Therapies.Biologics : targets & therapy · 2025Review
- Myeloid-driven immunosuppression in head and neck cancer: single-cell ATAC/RNA and spatial transcriptomic perspectives.Frontiers in oncology · 2025Review
- Single-cell multimodal chromatin profiles revealing epigenetic regulations of cells in hepatocellular carcinoma.Clinical and translational discovery · 2024Article
- Recover then aggregate: unified cross-modal deep clustering with global structural information for single-cell data.Briefings in bioinformatics · 2024Article
- Technology-enabled great leap in deciphering plant genomes.Nature plants · 2024Review
- Single cell RNA-seq: a novel tool to unravel virus-host interplay.Virusdisease · 2024Review
- Biophysical Reviews: peering into 2024.Biophysical reviews · 2024Article
- Article
- Spatial multi-omics: novel tools to study the complexity of cardiovascular diseases.Genome medicine · 2024Review
- Mechanisms and technologies in cancer epigenetics.Frontiers in oncology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the rapid advance of single-cell sequencing technology, cell heterogeneity in various biological processes was dissected at different omics levels. However, single-cell mono-omics results in fragmentation of information and could not provide complete cell states. In the past several years, a variety of single-cell multimodal omics technologies have been developed to jointly profile multiple molecular modalities, including genome, transcriptome, epigenome, and proteome, from the same single cell. With the availability of single-cell multimodal omics data, we can simultaneously investigate the effects of genomic mutation or epigenetic modification on transcription and translation, and reveal the potential mechanisms underlying disease pathogenesis. Driven by the massive single-cell omics data, the integration method of single-cell multi-omics data has rapidly developed. Integration of the massive multi-omics single-cell data in public databases in the future will make it possible to construct a cell atlas of multi-omics, enabling us to comprehensively understand cell state and gene regulation at single-cell resolution. In this review, we summarized the experimental methods for single-cell multimodal omics data and computational methods for multi-omics data integration. We also discussed the future development of this field.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.