ReviewFrontiers in bioinformatics2024
A systematic overview of single-cell transcriptomics databases, their use cases, and limitations.
Review in Frontiers in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- SC-framework: A robust and FAIR semi-interactive environment for single-cell resolution datasets.iScience · 2026Article
- A unified single-cell atlas of HNSCC: Toward characterizing HPV- and sex-associated TME variability.iScience · 2026Article
- Assessing the performance of multimodal large language models in experimental information extraction from liquid-liquid phase separation literature.Scientific reports · 2026Article
- TEDD 2.0: an advanced temporal gene expression database enabled by in-silico functional analyses for developmental mechanism investigation.Science China. Life sciences · 2026Article
- ArchetypeShift: An R Package Integrating KEGG-Informed Pathway Analysis and IPA-Derived Functional Predictions for Validation of Single-Cell Archetypes.Bioinformatics and biology insights · 2026Article
- Single-cell sequencing and organoids: applications in organ development and disease.Molecular biomedicine · 2025Review
- Galaxy single-cell & spatial omics community update: Navigating new frontiers in 2025.Cell genomics · 2025Review
- Single-Cell Transcriptomic Approaches for Decoding Non-Coding RNA Mechanisms in Colorectal Cancer.Non-coding RNA · 2025Review
- Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients.Scientific data · 2025Article
- Article
- Decoding congenital heart disease: a multi-omic framework for cardiac lineage and regulatory dysfunction.Frontiers in cell and developmental biology · 2025Review
- Bronchoalveolar lavage single-cell transcriptomics reveals immune dysregulations driving COVID-19 severity.PloS one · 2025Article
- Machine Learning and Mendelian Randomization Identify Allergic Rhinitis as Nasopharyngeal Carcinoma Risk Factor With Validated Potential Candidate Biomarkers.International journal of genomics · 2025Article
- RNA-based diagnostic innovations: A new frontier in diabetes diagnosis and management.Diabetes & vascular disease researchReview
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4 authors.
Funding
Abstract
Rapid advancements in high-throughput single-cell RNA-seq (scRNA-seq) technologies and experimental protocols have led to the generation of vast amounts of transcriptomic data that populates several online databases and repositories. Here, we systematically examined large-scale scRNA-seq databases, categorizing them based on their scope and purpose such as general, tissue-specific databases, disease-specific databases, cancer-focused databases, and cell type-focused databases. Next, we discuss the technical and methodological challenges associated with curating large-scale scRNA-seq databases, along with current computational solutions. We argue that understanding scRNA-seq databases, including their limitations and assumptions, is crucial for effectively utilizing this data to make robust discoveries and identify novel biological insights. Such platforms can help bridge the gap between computational and wet lab scientists through user-friendly web-based interfaces needed for democratizing access to single-cell data. These platforms would facilitate interdisciplinary research, enabling researchers from various disciplines to collaborate effectively. This review underscores the importance of leveraging computational approaches to unravel the complexities of single-cell data and offers a promising direction for future research in the 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.