😀Welcome
A brief intro to cryoSTAR
Last updated
A brief intro to cryoSTAR
Last updated
Hi there! 👋
This is cryoSTAR, a neural network based framework for recovering conformational heterogenity of protein complexes. By leveraging the structural prior and constraints from a reference pdb model, cryoSTAR can output both the protein structure and density map.
Nov. 13, 2023. The detailed documentation is released.
This documentation provides comprehensive information to help you understand the significant aspects of the project and guides you to utilize our methods over various datasets. This documentation includes the following:
Installation Guide: Installation guide provide step-by-step directions to install cryoSTAR.
Guide to Using CryoSTAR on Simulated Data: A Minimal Case will equip you with all the necessary steps to employ our method on a benchmark simulated dataset generated by ourselves.
Guides to Using CryoSTAR on Two Real Datasets: A Real Case: EMPIAR-10180 offers in-depth tutorials on how to apply our unique methodologies over real dataset.
A Guide to Using CryoSTAR on Your Own Data: If you have your data and are unsure about deploying our method, this guide Try on Your Own Data! is here for you. We will walk you through the process and requirements to ensure you can effectively use our method on your individual dataset.
We look forward to you to make the most out of our resources and to benefit from our unique methodologies. Flavor your future projects with our open-source project, and let's embark on this fascinating journey together! 🚀✨👩💻
We are deeply thankful to Ellen Zhong, Sjors Scheres, Frédéric Poitevin, Axel Levy, along with many other individuals and organizations. Their significant contributions to open-source initiatives have made a great impact. Their collaborative and transparent approach to software development has been inspirational, influencing our project positively and considerably. Additionally, we express our appreciation to ChatGPT for its remarkable assistance in the creation of this document.
If you find this tool useful, please cite:
CryoSTAR: Leveraging Structural Prior and Constraints for Cryo-EM Heterogeneous Reconstruction
Yilai Li, Yi Zhou, Jing Yuan, Fei Ye, Quanquan Gu
bioRxiv 2023, https://www.biorxiv.org/content/10.1101/2023.10.31.564872v1