Advancing biological understanding of cellular senescence with computational multiomics.
Li S, Agudelo Garcia PA, Aliferis C, Becich MJ, Calyeca J, Cosgrove BD, Elisseeff J, Farzad N, Fertig EJ, Glass C, Gu L, Hu Q, Ji Z, Königshoff M, LeBrasseur NK, Li D, Ma A, Ma Q, Menon V, Mitchell JT, Mora AL, Nagaraj S, Nelson AC, Niedernhofer LJ, Rojas M, Taha HB, Wang J, Wang S, Wu PH, Xie J, Xu M, Yu M, Zhang X, Zhao Y, Adams PD, Aguayo-Mazzucato C, Baker DJ, Benz C, Bernlohr DA, Bueno M, Chen J, Childs BG, Chuang JH, Chung D, Dileepan M, Ding L, Dong M, Duncan F, Enninful A, Flynn WF, Franco AC, Furman D, Garovic V, Halene S, Herman AB, Hertzel AV, Iwasaki K, Jeon H, Kang JW, Karmakar S, Kirkland JL, Korstanje R, Kummerfeld E, Lee JH, Liu Y, Lu Y, Lugo-Martinez J, Martini H, Melov S, Musi N, Passos JF, Peters ST, Rahman I, Ramasamy R, Rindone AN, Robbins PD, Robson P, Rodriguez-Lopez J, Rosas L, Rosenthal N, Schafer MJ, Schilling B, Schmidt EL, Schneider K, Sengupta K, Shu J, So PTC, Sun L, Tchkonia T, Teneche MG, Vanegas N, Wang J, Xie J, Yin S, Zhang K, Zhu Q, Fan R; SenNet Consortium.
Li S, et al.
Nat Genet. 2025 Oct;57(10):2381-2394. doi: 10.1038/s41588-025-02314-y. Epub 2025 Sep 15.
Nat Genet. 2025.
PMID: 40954249
Review.
