Chemotaxis-driven Instabilities govern size, shape and migration efficiency of multicellular clusters

This dataset documents experimental and simulation-based measurements of collective chemotactic migration and dynamical behavior of multicellular cell clusters. It includes processed experimental data derived from time-lapse microscopy of chronic lymphocytic leukemia (CLL) cell clusters exposed to controlled gradients of the chemokine CCL19 (0–100 ng ml⁻¹ mm⁻¹). Image-based measurements were extracted using Fiji/ImageJ and include cluster size, centroid trajectories, migration velocities, shape descriptors, and orientation of the cluster’s major axis relative to the chemical gradient, reported in pixel units. The dataset also contains processed outputs from particle-based and agent-based simulations spanning multiple cluster sizes and gradient strengths. Simulation variables include forward migration index, mixing entropy, spatial and orientational correlations, shape metrics, rotational dynamics, and cluster breaking frequencies. Scripts used to compute quantitative metrics and reprodu..., , # Chemotaxis-driven Instabilities govern size, shape and migration efficiency of multicellular clusters

Dataset DOI: [10.5061/dryad.612jm64k7](https://doi.org/10.5061/dryad.612jm64k7)

## Description of the data and file structure

This dataset accompanies the article *“Chemotaxis-driven instabilities govern size, shape and migration efficiency of multicellular clusters”* and contains experimental and simulation data quantifying collective chemotactic migration, shape deformation, orientation, and breakup of multicellular clusters. Experimental data were obtained from time-lapse microscopy of chronic lymphocytic leukemia (CLL) cell clusters exposed to controlled CCL19 gradients (0–100 ng ml⁻¹ mm⁻¹). Processed measurements extracted using Fiji/ImageJ include cluster size, centroid position, shape metrics, and the orientation of the major axis relative to the chemical gradient, reported in pixel units. Simulation data consist of processed outputs from agent-based models spanning multiple...,