ArticleNucleic acids research2024
DiSignAtlas: an atlas of human and mouse disease signatures based on bulk and single-cell transcriptomics.
Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 9 citations in OpenAlex.
- Literature-derived, context-aware gene regulatory networks improve biological predictions and mathematical modeling.Bioinformatics (Oxford, England) · 2026Article
- ChEA-KG and ChEA-KG-TS: a network-based transcription factor enrichment analysis tool with an accompanying time-series workflow.Nucleic acids research · 2026Article
- RD-OMICS: An Integrative Multi-Omics Data Inventory in Rare Diseases.bioRxiv : the preprint server for biology · 2026Article
- Type I interferon-dependent and -independent signaling underlie autoantibody production in a murine lupus model.Journal of translational autoimmunity · 2026Article
- A Scalable Sign-Aware Multi-Omics Knowledge Graph Foundation Model for Mechanistic Drug Action and Clinical Response Predictions.bioRxiv : the preprint server for biology · 2026Article
- Ubiquitin-conjugating enzyme E2S serves as a prognostic marker for skin cutaneous melanoma.Translational cancer research · 2025Article
- SCENE: Signature Collection for Endometrial Cancer Prognosis.Journal of cellular and molecular medicine · 2025Review
- STCDB4ND: a signal transduction classification database for neurological diseases.Database : the journal of biological databases and curation · 2025Article
- ID-GBA: Subgraph Extension With Information Distance Guilt by Association in Complex Networks.IEEE access : practical innovations, open solutions · 2025Article
- RummaGEO: Automatic mining of human and mouse gene sets from GEO.Patterns (New York, N.Y.) · 2024Article
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Authors and funding
15 authors at 2 institutions in 1 country.
Funding
Abstract
Molecular signatures are usually sets of biomolecules that can serve as diagnostic, prognostic, predictive, or therapeutic markers for a specific disease. Omics data derived from various high-throughput molecular biology technologies offer global, unbiased and appropriately comparable data, which can be used to identify such molecular signatures. To address the need for comprehensive disease signatures, DiSignAtlas (http://www.inbirg.com/disignatlas/) was developed to provide transcriptomics-based signatures for a wide range of diseases. A total of 181 434 transcriptome profiles were manually curated from studies involving 1836 nonredundant disease types in humans and mice. Then, 10 306 comparison datasets comprising both disease and control samples, including 328 single-cell RNA sequencing datasets, were established. Furthermore, a total of 3 775 317 differentially expressed genes in humans and 1 723 674 in mice were identified as disease signatures by analysing transcriptome profiles using commonly used pipelines. In addition to providing multiple methods for the retrieval of disease signatures, DiSignAtlas provides downstream functional enrichment analysis, cell type analysis and signature correlation analysis between diseases or species when available. Moreover, multiple analytical and comparison tools for disease signatures are available. DiSignAtlas is expected to become a valuable resource for both bioscientists and bioinformaticians engaged in translational research.
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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.