4D spatiotemporal landscape of mitochondrial phenotypes across cellular states unlocked through representation learning.
PubMed / NCBI E-utilities · 學術索引收錄 · 來源發佈：Thu Sep 10 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · 本站收錄：Thu Oct 08 2026 09:08:08 GMT+0000 (Coordinated Universal Time)
已保存的原文節選
Mitochondria are four-dimensional (4D: x, y, z, and time) organelles essential for cellular function. Characterizing their 4D phenotypic landscape across diverse cellular states requires both 4D imaging and analytical frameworks. We present MitoSpace, a self-supervised deep learning model trained without labels on terabytes of single-cell lattice light-sheet microscopy data of mitochondria under m
以上為帶出處的原文節選，完整內容請閱讀原始鏈接。自動收錄與主題分類不等於事實核驗。