SIGNOR 3.0, the SIGnaling Network Open Resource 3.0: 2022 Update
Overview
Authors
Affiliations
The SIGnaling Network Open Resource (SIGNOR 3.0, https://signor.uniroma2.it) is a public repository that captures causal information and represents it according to an 'activity-flow' model. SIGNOR provides freely-accessible static maps of causal interactions that can be tailored, pruned and refined to build dynamic and predictive models. Each signaling relationship is annotated with an effect (up/down-regulation) and with the mechanism (e.g. binding, phosphorylation, transcriptional activation, etc.) causing the regulation of the target entity. Since its latest release, SIGNOR has undergone a significant upgrade including: (i) a new website that offers an improved user experience and novel advanced search and graph tools; (ii) a significant content growth adding up to a total of approx. 33,000 manually-annotated causal relationships between more than 8900 biological entities; (iii) an increase in the number of manually annotated pathways, currently including pathways deregulated by SARS-CoV-2 infection or involved in neurodevelopment synaptic transmission and metabolism, among others; (iv) additional features such as new model to represent metabolic reactions and a new confidence score assigned to each interaction.
Ying H, Wu X, Jia X, Yang Q, Liu H, Zhao H EBioMedicine. 2025; 113:105596.
PMID: 39933264 PMC: 11867302. DOI: 10.1016/j.ebiom.2025.105596.
Minaeva M, Domingo J, Rentzsch P, Lappalainen T NAR Genom Bioinform. 2025; 7(1):lqae178.
PMID: 39781510 PMC: 11704787. DOI: 10.1093/nargab/lqae178.
Ki-67 and CDK1 control the dynamic association of nuclear lipids with mitotic chromosomes.
Hu H, Wang U, Chen B, Hsueh Y, Wang T J Lipid Res. 2024; 66(1):100731.
PMID: 39706365 PMC: 11786767. DOI: 10.1016/j.jlr.2024.100731.
State of the interactomes: an evaluation of molecular networks for generating biological insights.
Wright S, Colton S, Schaffer L, Pillich R, Churas C, Pratt D Mol Syst Biol. 2024; 21(1):1-29.
PMID: 39653848 PMC: 11697402. DOI: 10.1038/s44320-024-00077-y.
LM-Merger: A workflow for merging logical models with an application to gene regulation.
Li L, Aguilar B, Gennari J, Qin G bioRxiv. 2024; .
PMID: 39345612 PMC: 11429764. DOI: 10.1101/2024.09.13.612961.