ReviewTrends in biotechnology2020
Integrative Methods and Practical Challenges for Single-Cell Multi-omics.
Review in Trends in biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 154 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
154 citing papers in PubMed, 3 syntheses or guidelines pooled it, 279 citations in OpenAlex.
- Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective.Briefings in bioinformatics · 2025Pooled it
- Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data.Genome biology · 2023Pooled it
- Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages.International journal of molecular sciences · 2020Pooled it
- Article
- scGSI: Graph-guided self-supervised integration of paired single-cell multi-omics.PLoS computational biology · 2026Article
- A deep learning and large language hybrid workflow for omics interpretation.Nature biomedical engineering · 2026Article
- Integrating Single-Cell Sequencing and Proteomics to Unravel Stem Cell Heterogeneity: Implications for Precision Regenerative Medicine.Stem cell reviews and reports · 2026Review
- Tumor microenvironment-specific nanomedicine: from biology-driven to multi-omics-guided precision engineering.Journal of hematology & oncology · 2026Review
- Leveraging single-cell and spatial omics for brain tumour insights to improve therapeutic strategies.Molecular brain · 2026Review
- Graph designs for deep learning-based multi-omics integration.Briefings in bioinformatics · 2026Review
- Semi-supervised disentangled representation learning for single-cell RNA sequencing data.Briefings in bioinformatics · 2026Article
- Mechanisms and precision interventions in sarcopenia and osteoarthritis comorbidity: A narrative review.Journal of orthopaedic translation · 2026Review
- A multi-modal diffusion model with dual-cross-attention for multi-omics data generation and translation.Nature communications · 2026Article
- Dissecting Normal and Abnormal Human Kidney Development Using Multiomics.Journal of the American Society of Nephrology : JASN · 2026Review
- scII: Dual-Threshold Adaptive Integration of Single-Cell Multiomics Data Driven by Imputation.Journal of chemical information and modeling · 2026Article
- Opportunities for RNA sequencing in physiology: from big data to understanding homeostasis and heterogeneity.Function (Oxford, England) · 2026Review
- Srnc: semi-supervised learning for robust novel cell-type identification in single cell RNA sequencing data.BMC bioinformatics · 2026Article
- Adaptive multi-view information bottleneck for multi-omics data clustering.Briefings in bioinformatics · 2026Article
- Multi-omics to study chronic respiratory diseases and viral infections.European respiratory review : an official journal of the European Respiratory Society · 2026Review
- Leveraging Hamiltonian neural flow for robust single-cell multi-omics integration: application to Alzheimer's disease.Frontiers in genetics · 2026Article
94 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Fast-developing single-cell multimodal omics (scMulti-omics) technologies enable the measurement of multiple modalities, such as DNA methylation, chromatin accessibility, RNA expression, protein abundance, gene perturbation, and spatial information, from the same cell. scMulti-omics can comprehensively explore and identify cell characteristics, while also presenting challenges to the development of computational methods and tools for integrative analyses. Here, we review these integrative methods and summarize the existing tools for studying a variety of scMulti-omics data. The various functionalities and practical challenges in using the available tools in the public domain are explored through several case studies. Finally, we identify remaining challenges and future trends in scMulti-omics modeling and analyses.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.