{
  "id": 5292143,
  "title": "AnnFlux: object-conditioned neural stochastic differential equations for single-cell perturbation dynamics",
  "url": "https://urgent.news/2026/09/03/annflux-object-conditioned-neural-stochastic-differential-equations",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-03T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.01.748703v1?rss=1"
  },
  "original_language": "en",
  "account": "Single-cell perturbation profiling measures cellular responses to genetic and chemical interventions. However, most models used for this purpose learn a static map, failing to account for how cell populations evolve over time and how multiple perturbations interact. AnnFlux, a novel approach, learns a drift field in the latent cell-state space. By conditioning on the specific perturbing object, AnnFlux can query the field one object at a time, resulting in per-object drifts that are comparable across genes and drugs. This tailored drift field allows AnnFlux to interpolate data from a held-out timepoint in an epithelial-mesenchymal transition time course and predict unseen perturbations. Furthermore, AnnFlux enhances distributional fidelity and accurately predicts responses to combinations of held-out perturbations. An example of its predictive power is demonstrated by a predicted IFN-response signature that was later found to be associated with transcriptional landscape proximity in an independent pan-cancer spatial atlas. Ultimately, AnnFlux offers a framework for mapping the perturbation-driven evolution of cell states as continuous trajectories, and represents unseen perturbations using prior-knowledge embeddings.",
  "summary": "Single-cell perturbation profiling measures responses to genetic and chemical interventions, yet most models learn a static map, ignoring how populations move over time and how perturbations combine. AnnFlux, an object-conditioned stochastic differential equation, learns a drift field in latent cell-state space. Conditioning on the perturbing object makes the field queryable one object at a time,…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}