User friendly and accurate binder design pipeline
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Updated
Sep 21, 2026 - Jupyter Notebook
User friendly and accurate binder design pipeline
Jupyter Notebooks for learning the PyRosetta platform for biomolecular structure prediction and design
Automated, modular pipeline for de novo protein binder design on SLURM clusters, with the BFmonitor dashboard
RosettaDesign using PyRosetta
Using Rotamer Interaction Fields from RIFGen/Dock in python
Protein Structure prediction using Hybrid Differential Evolution (HybridDE)
A Rosetta-based Python tool for constructing user-defined variant libraries with amino acid insertions, deletions, using loop closure algorithms and energy minimization.
Method-independent benchmark of five de novo protein binder design tools on HPC
Structural bioinformatics pipeline for clustering antibody-antigen epitopes by geometric similarity and deriving consensus paratope design constraints for antibody engineering.
Computes biophysical metrics from monomeric PDB structures for use as features in machine learning models.
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