SenSASP

How to Cite SenSASP

If you use SenSASP data in your research, please cite the primary paper and acknowledge the upstream resources below. Proper citation helps sustain this resource.

Primary Citation (APA)

Xuan, H., Huang, Y., & Bian, J. (2026). SenSASP: A Unified, Multi-Layer Database of Senescence and SASP Genes. bioRxiv 2026.08.26.747427. https://doi.org/10.64898/2026.08.26.747427

BibTeX

@article{Xuan2026.08.26.747427, author = {Xuan, Hao and Huang, Yu and Bian, Jiang}, title = {SenSASP: A Unified, Multi-Layer Database of Senescence and SASP Genes}, elocation-id = {2026.08.26.747427}, year = {2026}, doi = {10.64898/2026.08.26.747427}, publisher = {Cold Spring Harbor Laboratory}, URL = {https://www.biorxiv.org/content/early/2026/09/11/2026.08.26.747427}, eprint = {https://www.biorxiv.org/content/early/2026/09/11/2026.08.26.747427.full.pdf}, journal = {bioRxiv} }

Data Availability Statement

Copy-paste this template into the Data Availability section of your manuscript:

The SenSASP unified cellular senescence / SASP gene database, including all 1,250 gene entries with multi-layer conservation, expression, and protein interaction annotation, is freely accessible at https://xuan13hao.github.io/sensasp and archived on GitHub at https://github.com/xuan13hao/sensasp.

Database Information

Genes
1,250 unique entries
Build date
2026-07-19
License
CC BY 4.0
Organism
Homo sapiens
Web
xuan13hao.github.io/sensasp
GitHub
github.com/xuan13hao/sensasp

Seed Sources — Please Also Cite

SenSASP integrates data from four existing databases. When you use genes from a specific source, please also cite that source directly:

SourceReferenceURL
CellAge Avelar, R. A., et al. (2020). A multidimensional systems biology analysis of cellular senescence in aging and disease. Genome Biology, 21(1), 91. doi:10.1186/s13059-020-01990-9 HAGR CellAge ↗
GenAge Tacutu, R., et al. (2018). Human Ageing Genomic Resources: new and updated databases. Nucleic Acids Research, 46(D1), D1083–D1090. doi:10.1093/nar/gkx1042 HAGR GenAge ↗
SenMayo Saul, D., et al. (2022). A new gene set identifies senescent cells and predicts senescence-associated pathways across tissues. Nature Communications, 13(1), 4827. doi:10.1038/s41467-022-32552-1 MSigDB ↗
Reactome Milacic, M., et al. (2024). The Reactome Pathway Knowledgebase 2024. Nucleic Acids Research, 52(D1), D672–D678. doi:10.1093/nar/gkad1025 R-HSA-2559583 ↗

Annotation Data Sources

LayerResource
Identifiers MyGene.info — Xin, J., et al. (2016). High-performance web services for querying gene and variant annotation. Genome Biology, 17(1), 91. doi:10.1186/s13059-016-0953-9
Conservation Ensembl Compara / BioMart — Cunningham, F., et al. (2022). Ensembl 2022. Nucleic Acids Research, 50(D1), D988–D995. doi:10.1093/nar/gkab1049
Expression (GTEx) GTEx Consortium (2020). The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science, 369(6509), 1318–1330. doi:10.1126/science.aaz1776
Expression (HPA) Uhlén, M., et al. (2015). Tissue-based map of the human proteome. Science, 347(6220), 1260419. doi:10.1126/science.1260419
Interactions STRING v12.0 — Szklarczyk, D., et al. (2023). The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any of 12,535 organisms. Nucleic Acids Research, 51(D1), D638–D646. doi:10.1093/nar/gkac1000