Back to search

Article

A machine learning framework for predicting and modulating condition-dependent protein phase separation

2025-12-29

Abstract excerpt

Protein phase separation is a fundamental process in organizing membraneless organelles and is implicated in a wide range of pathological conditions. Importantly, rather than being a static feature of specific proteins, phase separation is a condition-dependent phenomenon governed by environmental parameters, including protein concentration, temperature, and solvent composition. However, most existing machine lear...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
ba6df271-bf44-56a8-adff-d32b0b4b0a8d
DOI
10.64898/2025.12.28.696755
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
A machine learning framework for predicting and modulating condition-dependent protein phase separationDOI 10.64898/2025.12.28.696755
Select a neighboring publication to make it the new centre.