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  # RF*diffusion*
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  ## Description
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- RFdiffusion is an open source method for structure generation, with or without conditional information (a motif, target etc). It can perform a whole range of protein design challenges as we have outlined in [the RFdiffusion paper](https://www.biorxiv.org/content/10.1101/2022.12.09.519842v1).
 
 
 
 
 
 
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  **Things Diffusion can do**
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  - Motif Scaffolding
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  ### Partial diffusion
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- Something we can do with diffusion is to partially noise and de-noise a structure, to get some diversity around a general fold. This can work really nicely (see [Vazquez-Torres et al., BioRxiv 2022](https://www.biorxiv.org/content/10.1101/2022.12.10.519862v4.abstract)).
 
 
 
 
 
 
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  This is specified by using the diffuser.parial_T input, and setting a timestep to 'noise' to.
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  <img src="./img/partial.png" alt="alt text" width="800px" align="middle"/>
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  RFdiffusion builds directly on the architecture and trained parameters of RoseTTAFold. We therefore thank Frank DiMaio and Minkyung Baek, who developed RoseTTAFold.
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- RFdiffusion is released under an open source BSD License (see LICENSE file). It is free for both non-profit and for-profit use.
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+ ---
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+ license: apache-2.0
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+ datasets:
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+ - nvidia/PhysicalAI-Autonomous-Vehicles
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+ language:
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+ - en
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+ metrics:
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+ - accuracy
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+ base_model:
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+ - facebook/sam3
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+ new_version: facebook/sam3
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+ pipeline_tag: feature-extraction
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+ library_name: diffusers
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+ tags:
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+ - biology
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+ ---
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  # RF*diffusion*
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  <!--
 
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  ## Description
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+ RFdiffusion is an open source method for structure generation, with or without conditional information (a motif, target etc). It can perform a whole range of protein design challenges as we have outlined in [the RFdiffusion paper](https://www.biorxiv.org/content/10.1101/2022.12.09.519842v1
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+ ).
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  **Things Diffusion can do**
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  - Motif Scaffolding
 
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  ---
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  ### Partial diffusion
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+ Something we can do with diffusion is to partially noise and de-noise a structure, to get some diversity around a general fold. This can work really nicely (see [Vazquez-Torres et al., BioRxiv 2022](https://www.biorxiv.org/content/10.1101/2022.12.10.519862v4.abstract
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+ )).
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  This is specified by using the diffuser.parial_T input, and setting a timestep to 'noise' to.
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  <p align="center">
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  <img src="./img/partial.png" alt="alt text" width="800px" align="middle"/>
 
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  ---
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  RFdiffusion builds directly on the architecture and trained parameters of RoseTTAFold. We therefore thank Frank DiMaio and Minkyung Baek, who developed RoseTTAFold.
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+ RFdiffusion is released under an open source BSD License (see LICENSE file). It is free for both non-profit and for-profit use.