ArticleiScience2024
scMoresDB: A comprehensive database of single-cell multi-omics data for human respiratory system.
Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed, 4 citations in OpenAlex.
- The Impact of Genetics on Pediatric Interstitial Lung Diseases: A Narrative Literature Review and Clinical Implications.Biomedicines · 2026Review
- hECA v2.0: an AI-ready ensemble cell atlas of single-cell RNA and ATAC sequencing data.Scientific data · 2025Article
- Single-cell insights into tumor microenvironment heterogeneity and plasticity: transforming precision therapy in gastrointestinal cancers.Journal of experimental & clinical cancer research : CR · 2025Review
- Review
- Advances in modeling cellular state dynamics: integrating omics data and predictive techniques.Animal cells and systems · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The human respiratory system is a complex and important system that can suffer a variety of diseases. Single-cell sequencing technologies, applied in many respiratory disease studies, have enhanced our ability in characterizing molecular and phenotypic features at a single-cell resolution. The exponentially increasing data from these studies have consequently led to difficulties in data sharing and analysis. Here, we present scMoresDB, a single-cell multi-omics database platform with extensive omics types tailored for human respiratory diseases. scMoresDB re-analyzes single-cell multi-omics datasets, providing a user-friendly interface with cross-omics search capabilities, interactive visualizations, and analytical tools for comprehensive data sharing and integrative analysis. Our example applications highlight the potential significance of BSG receptor in SARS-CoV-2 infection as well as the involvement of HHIP and TGFB2 in the development and progression of chronic obstructive pulmonary disease. scMoresDB significantly increases accessibility and utility of single-cell data relevant to human respiratory system and associated diseases.
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.