SFold v0.1

Prince, Stephanie [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]; Tritt, Andrew [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]; Ruebel, Oliver [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]; Tsutakawa, Susan [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]; Yu, Feng [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]

doi:10.11578/dc.20251024.7

DOE OSTI · code-168250

SFold v0.1

Prince, Stephanie [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]·Tritt, Andrew [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]·Ruebel, Oliver [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]·Tsutakawa, Susan [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]·Yu, Feng [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]

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Abstract

This is a scientific software package to integrate Small Angle X-ray Scattering (SAXS) experimental data into OpenFold deep learning models to improve protein structure prediction.

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Prince, Stephanie [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Tritt, Andrew [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Ruebel, Oliver [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Tsutakawa, Susan [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Yu, Feng [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]. 2025-10-23. SFold v0.1. https://doi.org/10.11578/dc.20251024.7

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