ArticleNucleic acids research2026
SIGNOR 4.0: the 2025 update with focus on phosphorylation data.
Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Redefining 3D cell culture: Human methacryloyl platelet lysates hydrogels for reliable, consistent, and ethical applications.Materials today. Bio · 2026Article
- MultiOmicsXplorer, a tool to browse, access and analyse multi-omics data.BMC bioinformatics · 2026Article
- Human CD3 complex is required for the generation of T-cell receptor-like chimeric antigen receptor targeting WT1 in natural killer cells.Cancer immunology, immunotherapy : CII · 2026Article
- Modulation of Network Plasticity Opens Novel Therapeutic Possibilities in Cancer, Diabetes, and Neurodegeneration.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- KGBN: Augmenting and optimizing logical gene regulatory networks using knowledge graphs.bioRxiv : the preprint server for biology · 2026Article
- The 2026 Nucleic Acids Research database issue and the online molecular biology database collection.Nucleic acids research · 2026Article
- Stratified signaling network remodeling of kinase-transcription factors' interactions in Parkinson's disease.Bioinformatics advances · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
The SIGnaling Network Open Resource (SIGNOR 4.0, https://signor.uniroma2.it) is a database of manually curated causal interactions between biological entities. These signaling events are annotated along with their effect-denoting the activation or inactivation of a target entity-and mechanism through which it is mediated, such as phosphorylation, binding, or transcriptional regulation. The data is freely accessible and can be explored as customizable signaling networks, allowing users to adapt them for different modeling purposes. In our latest update (version 4.0), we improved our curation interface to include additional data-validation tools, integrated text-mining-assisted curation, increased our curation content, and expanded the scope of our curation efforts, with a particular emphasis on phosphorylation data. Furthermore, we developed a subdomain of SIGNOR, PhosphoSIGNOR, a dedicated user interface designed to enable targeted access to phosphorylation-specific information and network visualization. This expanded dataset allows for a more comprehensive mapping of signaling alterations and their associations with dysregulated cellular processes. The platform enables users to dynamically query phosphosite-specific data, examine context-dependent modifications, and integrate findings with known regulatory mechanisms. The PhosphoSIGNOR section of SIGNOR serves as an essential resource for cancer systems biology, offering an intuitive interface for hypothesis generation and mechanistic insights.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.