AlphaFold Unofficial Wiki

The provided code snippet forms a critical component of an automated script aimed at facilitating the prediction of protein structures using the AlphaFold model within a Google Colab environment. The script is tailored to handle the simultaneous upload of multiple input files, each containing multiple protein sequences for prediction.

Predict protein folding structures using ColabFold. Gain a deeper understanding of protein folding prediction with AlphaFold2 and MMseqs2. Run the Jupyter notebook on UCloud, learn to interpret results, predict protein structures of interest. Technical requirements provided. Enhance your knowledge of protein folding and AlphaFold2's principles. Fam

Open source code for AlphaFold.

Prediction of possible paths of gene mutation using AlphaFold

Investigate the role of mtDNA in the sex determination/development of Potamilus streckersoni, a freshwater mussel with doubly uniparental mitochondrial inheritance. Scripts for DESeq2, WGCNA, GSEA, AlphaFold/AlphaPulldown, and mt-sncRNA validation.

Establishing and testing AlphaFold on GPU

AlphaFold predictions of protein structure on Sydney Research Compute Infrastructure

Serotonin pathways interaction networks

AlphaFold-wrapper for small HPC

Reliable AlphaFold Measures

This repo contains a random forest, a convolutional neural network, and a graph convolutional neural network which predict the binding interaction between olfactory proteins and various chemicals using Alphafold predicted structural data.

Repository with scripts and data generated during my internship at Institut Pasteur of Paris

A proof-of-concept for using AlphaFold with new amino acid sequences (this may change to a full project in the future).

Colabfold setup and scripts

Protein representation learning using graph neural networks and Alphafold generated 3D structures.

This package provides an basic implementation of the contact prediction network used in AlphaFold 1 for beginner, associated model weights and CASP13 dataset as used for CASP13 (2018) and published in Nature

Stand-alone server for structural proteome curation

Examines ligand interactions with predicted protein structures