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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Yuejiang Yu
About me
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Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
hobbies
Calligraphy Work 1: Orchid Pavilion Preface
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Orchid Pavilion Preface is a piece of Chinese calligraphy work generally considered to be written by the well-known calligrapher Wang Xizhi (303 – 361) from the Eastern Jin dynasty (317 – 420). Below is my copy: 
publications
Uni-Dock: A GPU-Accelerated Docking Program Enables Ultra-Large Virtual Screening
Published in ChemRxiv, 2022
Based on CUDA, Uni-Dock achieved more than 1600 times acceleration on GPU compared to CPU and saved five times the cost without losing accuracy. Integrated into advanced industrial Computer-aided drug design (CADD) product, Uni-Dock enables ultra-large virtual screening of early-stage drug discovery in hours, used by hundreds of chemists.
Recommended citation: Yuejiang, Yu. (2022). "Uni-Dock: A GPU-Accelerated Docking Program Enables Ultra-Large Virtual Screening." Accepted by ACS JCTC. https://doi.org/10.26434/chemrxiv-2022-5t5ts
Do deep learning models really outperform traditional approaches in molecular docking?
Published in ICLR 2023 MLDD workshop(oral), 2023
We benchmark deep learning models and traditional methods for molecular docking, and find traditional methods are still better.
Recommended citation: Yuejiang, Yu. (2023). "Do deep learning models really outperform traditional approaches in molecular docking?" ICLR 2023 MLDD workshop(oral). https://arxiv.org/abs/2302.07134
Uni-Dock: GPU-Accelerated Docking Enables Ultra-Large Virtual Screening
Published in Journal of Chemical Theory and Computation, 2023
Based on CUDA, Uni-Dock achieved more than 1600 times acceleration on GPU compared to CPU and saved five times the cost without losing accuracy. Integrated into advanced industrial Computer-aided drug design (CADD) product, Uni-Dock enables ultra-large virtual screening of early-stage drug discovery in hours, used by hundreds of chemists.
Recommended citation: Yuejiang, Yu. (2023). "Uni-Dock: GPU-Accelerated Docking Enables Ultra-Large Virtual Screening." Journal of Chemical Theory and Computation 19.11 (2023). [https://doi.org/10.26434/chemrxiv-2022-5t5ts](https://pubs.acs.org/doi/abs/10.1021/acs.jctc.2c01145)
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.