SUPR
Modeling cell signaling dynamic
Dnr:

NAISS 2025/22-405

Type:

NAISS Small Compute

Principal Investigator:

Aurora Poggi

Affiliation:

Kungliga Tekniska högskolan

Start Date:

2025-03-12

End Date:

2025-09-01

Primary Classification:

10105: Computational Mathematics

Webpage:

Allocation

Abstract

The project aim to develop a framework based on various theories to infer (reverse engineering) a dynamical system from discrete observations of its states. These discrete observations are provided in the form of highly noisy time series of 2D microscopy images. Using theory based on Takens Embedding theorem to compute the dimension of the attractor and characterize its geometry.