Integrative proteomic and machine learning strategies identify key biomarkers associated with response to JAK inhibitor in rheumatoid arthritis.
- DOI
- 10.1186/s13075-026-03880-0
- Published
- 2026 Aug 4
- Container
- Arthritis research & therapy
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1186/s13075-026-03880-0,
title = {Integrative proteomic and machine learning strategies identify key biomarkers associated with response to JAK inhibitor in rheumatoid arthritis.},
author = {Chen SF and Wu TS and Chang KY and Lo SM and Chen YT and Kao CM and Chen YJ and Chang HY and Chen YM},
year = {2026},
journal = {Arthritis research \& therapy},
doi = {10.1186/s13075-026-03880-0},
url = {https://doi.org/10.1186/s13075-026-03880-0}
}RIS
TY - JOUR TI - Integrative proteomic and machine learning strategies identify key biomarkers associated with response to JAK inhibitor in rheumatoid arthritis. AU - Chen SF AU - Wu TS AU - Chang KY AU - Lo SM AU - Chen YT AU - Kao CM AU - Chen YJ AU - Chang HY AU - Chen YM PY - 2026 JO - Arthritis research & therapy DO - 10.1186/s13075-026-03880-0 UR - https://doi.org/10.1186/s13075-026-03880-0 ER -
APA
SF, C., TS, W., KY, C., SM, L., YT, C., CM, K., YJ, C., HY, C., & YM, C. (2026). Integrative proteomic and machine learning strategies identify key biomarkers associated with response to JAK inhibitor in rheumatoid arthritis.. Arthritis research & therapy. https://doi.org/10.1186/s13075-026-03880-0
Source records
- pubmed · retrieved 2026-11-10T14:21:49.357Z