Field-theoretic simulation and random phase approximation Python codes for polyampholyte phase-separation
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Updated
Jul 23, 2024 - Python
Field-theoretic simulation and random phase approximation Python codes for polyampholyte phase-separation
A Python package for field theoretic simulations of biomolecular phase-separation
An Experiment-Informed HDP-HMM to Analyze Surface-Immobilized smFRET Data
PyHeteroMap: A python package that maps and analyzes the conformational ensembles of Intrinsically Disordered Proteins (IDPs) from simulations.
a database of membrane binding sites in intrinsically disordered regions of human transmembrane proteins
MarkerPredict is a project to identify intrinsically disordered proteins as biomarkers of targeted cancer therapies with the use of network topology and motif identification. We created machine learning models using the Random Forest and XGBoost algorhythms that are able to predict new biomarkers based on biological annotation and topological data.
🧠🔬At the Cordeiro Lab, we investigate how intrinsically disordered proteins and biomolecular assemblies orchestrate cellular organization, pathogenic survival, and biotechnological innovation.
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