Gioele La Manno

中文導讀

Gioele La Manno 是 RNA velocity 的 origin 第一作者(velocyto-2018,La Manno et al., Nature 2018,當年在 Linnarsson lab),現在是 EPFL 的 PI(Laboratory of Brain Development and Biological Data Science)。對本 wiki 的敘事極關鍵:他 2018 把 velocity 定義成 physical ds/dt (hours,EdU labeling 校準),後繼 snapshot 方法把它變 ordinal latent time;2024 他又用 VeloCycle(velocycle-2024)把 physical time 用 statistical rigor 重新立起來—— manifold-constrained Bayesian model,在 cell cycle 上 reach metric time 並用 live-imaging 驗證。 也就是 origin → regression → recovery 這條 velocity-skepticism 主線,他本人走了一整圈。

Who they are

PI of the Laboratory of Brain Development and Biological Data Science at EPFL. As lead author of velocyto-2018 (in Sten Linnarsson’s lab) he founded RNA velocity, defining it as a physically interpretable time-derivative (ds/dt) of expression, with the extrapolation step calibrated to hours via EdU / metabolic labeling. He returns to the field with velocycle-2024 / VeloCycle (co-corresponding with FelixNaef), a manifold-constrained Bayesian reformulation that recovers validated metric cell-cycle time without metabolic labeling.

Why they matter to this wiki

He personally bookends the wiki’s origin-reframe / regression narrative:

  • 2018 (origin): velocity = physical rate in hours (velocyto-2018, metabolic-labeling).
  • 2020–2024 (regression): snapshot successors (scVelo latent time) drop the anchor; velocity becomes ordinal pseudo-time (the velocity-skepticism / JianhuaXing complaint).
  • 2024 (recovery): VeloCycle re-grounds metric time on the cell cycle with statistical control and live-imaging validation — the first direct real-time validation of RNA velocity.

That arc — from the field’s founder — is strong, citable support for FlowVelo positioning the temporal axis as the real open problem and metric time as attainable with constrained geometry + a rate anchor.

Connections