phase-separation

PyStokes: phoresis and Stokesian hydrodynamics in Python. github.com/rajeshrinet/pystokes

PyGL: statistical field theory in Python. github.com/rajeshrinet/pygl

This GitHub repository contains the code and data for the manuscript "Macromolecular Condensation Organizes Nucleolar Sub-Phases to Set Up a pH Gradient." Available at: https://www.cell.com/cell/fulltext/S0092-8674(24)00232-0

This is a Python package for classifying DAmFRET data based on supervised learning. The data can also be analyzed to allow mechanistic inferences regarding nucleation of ordered assemblies.

Studying the Ising model phase transition using PCA.

Multi-condensate state as a functional strategy to optimize the cell signaling output

Predict protein phase-separation propensity from amino-acid sequence — open implementation of Chen et al. 2022 PNAS

Simulation scripts used in the study "Separation of sticker-spacer energetics governs the coalescence of metastable biomolecular condensates"

Computational triage of novel ashless additives for ethanol-blended petrol (E10/E20). Surrogate-method course experiment.

Exploring the dynamics of liquid-liquid phase separation (LLPS) in a confined system with focusing on nonequilibrium condition and the broken of detailed balance (Phys.Rev.E)

Condensate detection and quantification for confocal microscopy of ER liquid‚Äìliquid phase separation. Olympus .oir ‚lossless TIFF ‚ LoG + watershed detection ‚ per-cell counts, sizes and IN/OUT ratios.

RG/RGG tract grammar analysis + figure-generation scripts, with CALVADOS v3 slab simulation post-processing

Research with the Spakowitz Research Group

Python framework for simulating physical systems consisting of multiple, interacting droplets.

Apply semi-implicit pseudo-spectral method to model the spinodal decomposition kinetics (based on Cahn-Hilliard framework) of a binary (polymer-solvent) and ternary (polymer-polymer-solvent) mixture

Predicting how sequence changes alter liquid-liquid phase separation: condition-aware, uncertainty-aware LLPS modelling

Reproducible 2D Kawasaki–Ising coarsening and a two-tier (spectral + coarsening) operational test of the Mpemba effect under conserved dynamics. Result: no Mpemba-like inversion.

This GitHub repository contains the code and data for the manuscript "Dynamical control enables the formation of demixed biomolecular condensates" (BioRxiv link: https://www.biorxiv.org/content/10.1101/2023.01.04.522702v1)

Code of project realized at the University of Geneva in the group of Karsten Kruse, in collaboration with the group of Charlotte Aumeier.