Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
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Updated
Aug 21, 2025 - Python
Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
Jupyter Notebooks for learning the PyRosetta platform for biomolecular structure prediction and design
Optimizing AlphaFold Training and Inference on GPU Clusters
IntelliFold: A Controllable Foundation Model for General and Specialized Biomolecular Structure Prediction.
Protein 3D structure prediction pipeline
🧬 ManyFold: An efficient and flexible library for training and validating protein folding models
FrameDiPT: an SE(3) diffusion model for protein structure inpainting
Example to fit parameters and run CG simulations using TorchMD and Schnet
Step-by-step guide to install and configure AlphaFold 3 using a Conda Python 3.11 environment. No system-wide installations required. ✅ Miniconda setup & dependencies ✅ Repository cloning & model setup ✅ Database configuration & execution script 🔹 Requirements: Linux, NVIDIA GPU (Ampere+), CUDA, ~700GB disk space.
Deep learning for protein science
Singularity recipe for AlphaFold
An interactive visual simulator for distance-based protein folding
Infrastructure template and Jupyter notebooks for running RoseTTAFold on AWS Batch.
OPUS-Fold: An Open-Source Protein Folding Framework Based on Torsion-Angle Sampling
A curated list of FREE courses available online from top universities of the world on Computational Biology and Bioinformatics.
Prospr is a universal toolbox for protein structure prediction within the HP-model. The Python package is based on a C++ core, which gives Prospr its high performance. The C++ core is made available as a separate zip file to facilitate high-performance computing applications. The package comes with many prediction algorithms and datasets to use.
Python package for generating Markov state models
A curated list of awesome protein design research, software and resources.
The largest open-source dataset for Protein Single Sequence Secondary Structure prediction.
Selecting Features for Markov Modeling: A Case Study on HP35
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