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Shayan Hajhashemi

Doctorat - McGill
Superviseur⋅e principal⋅e
Amin Emad
Sujets de recherche
Apprentissage par renforcement
Biologie computationnelle
Causalité
Modèles probabilistes
Optimisation
Réseaux de neurones en graphes
Systèmes dynamiques
Théorie de l'information
GitHub

Publications

A Latent Space Thermodynamic Model of Cell Differentiation
Ali Poursina
Shayan Hajhashemi
Arsham Mikaeili Namini
Alihossein Saberi
Amin Emad
Hamed S. Najafabadi
Abstract Inferring the governing dynamics of differentiation that capture cell state evolution remains a central challenge in single-cell bi… (voir plus)ology. We present Latent Space Dynamics (LSD), a thermodynamics-inspired framework that models cell differentiation as evolution on a learned Waddington landscape in latent space. LSD jointly infers a low-dimensional cell state, a differentiable potential function governing developmental flow, and a local entropy term that quantifies cellular plasticity. Using a neural ordinary differential equation, LSD reconstructs continuous differentiation trajectories from time-ordered single-cell data. Across diverse developmental systems, LSD accurately recovers lineage hierarchies, predicts fate commitment for unseen cell types, and outperforms existing trajectory inference approaches in directional accuracy. Moreover, in silico gene perturbations reveal how individual regulators reshape the landscape, and entropy provides a quantitative measure of plasticity in development and cancer.
2026-03-05
bioRxiv (prépublication)
doi.org