ReviewComputational and structural biotechnology journal2021
Computational strategies for single-cell multi-omics integration.
Review in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
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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.
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Who cites it
60 citing papers in PubMed.
- Target identification and assessment in the era of AI.Nature reviews. Drug discovery · 2026Review
- Leveraging single-cell and spatial omics for brain tumour insights to improve therapeutic strategies.Molecular brain · 2026Review
- Network methods for diagonal integration of unpaired single-cell multiomics data: a review.Bioinformatics (Oxford, England) · 2026Review
- CEDR: robust consensus cancer subtyping with multi-omics data via ensemble dimensionality reduction.Briefings in bioinformatics · 2026Article
- Graph designs for deep learning-based multi-omics integration.Briefings in bioinformatics · 2026Review
- Single Cell Analysis Reveals the Presence of Novel Intermediate Cells in Both Mice and Patients With Severe MASLD.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Mass Spectrometry Proteomics: A Key to Faster Drug Discovery.Journal of medicinal chemistry · 2026Review
- Adaptive multi-view information bottleneck for multi-omics data clustering.Briefings in bioinformatics · 2026Article
- Advancing precision immuno-oncology in melanoma: the synergistic convergence of personalized neoantigen vaccines and multi-omics biomarker profiling.Frontiers in immunology · 2026Review
- LIMPACAT: Multi-omics attention transformer for immune prediction in liver cancer using whole-slide imaging.PloS one · 2026Article
- Molecular mechanisms underlying T cell subset imbalance and precision therapeutic targets in primary biliary cholangitis.Frontiers in pharmacology · 2026Review
- GatorSC: Multi-Scale Cell and Gene Graphs with Mixture-of-Experts Fusion for Single-Cell Transcriptomics.bioRxiv : the preprint server for biology · 2025Article
- Integrating multi-omics data: Methods and applications in human complex diseases.Biotechnology reports (Amsterdam, Netherlands) · 2025Review
- Cellular and molecular mechanisms of seahorse male pregnancy.Nature ecology & evolution · 2025Article
- Multimodal single cell analyses reveal gene networks of planarian stem cell differentiation.Nature communications · 2025Article
- Multi-omics strategies for biomarker discovery and application in personalized oncology.Molecular biomedicine · 2025Review
- Dynamic Synthesis of Multi-Modal Representations for CITE-seq Data Integration and Analysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Integration of cell-type resolved spatial proteomics and transcriptomics reveals novel mechanisms in early ovarian cancer.medRxiv : the preprint server for health sciences · 2025Article
- scMultiNODE: Integrative and Scalable Framework for Multi-Modal Temporal Single-Cell Data.bioRxiv : the preprint server for biology · 2025Article
- The Potential Use of Digital Twin Technology for Advancing CAR-T Cell Therapy.Current issues in molecular biology · 2025Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell omics technologies are currently solving biological and medical problems that earlier have remained elusive, such as discovery of new cell types, cellular differentiation trajectories and communication networks across cells and tissues. Current advances especially in single-cell multi-omics hold high potential for breakthroughs by integration of multiple different omics layers. To pair with the recent biotechnological developments, many computational approaches to process and analyze single-cell multi-omics data have been proposed. In this review, we first introduce recent developments in single-cell multi-omics in general and then focus on the available data integration strategies. The integration approaches are divided into three categories: early, intermediate, and late data integration. For each category, we describe the underlying conceptual principles and main characteristics, as well as provide examples of currently available tools and how they have been applied to analyze single-cell multi-omics data. Finally, we explore the challenges and prospective future directions of single-cell multi-omics data integration, including examples of adopting multi-view analysis approaches used in other disciplines to single-cell multi-omics.
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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.