DeepSF: deep convolutional neural network for mapping protein sequences to folds

Protein fold recognition is an important problem in structural bioinformatics. Almost all traditional fold recognition methods use sequence (homology) comparison to indirectly predict the fold of a target protein based on the fold of a template protein with known structure, which cannot explain the relationship between sequence and fold. Only a few methods had been developed to classify protein sequences into a small number of folds due to methodological limitations, which are not generally useful in practice.

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Jie Hou, Badri Adhikari, Jianlin Cheng (2025). Dataset: DeepSF: deep convolutional neural network for mapping protein sequences to folds. https://doi.org/10.57702/qb396h2i

DOI retrieved: January 3, 2025

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Created January 3, 2025
Last update January 3, 2025
Defined In https://doi.org/10.48550/arXiv.1706.01010
Author Jie Hou
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Badri Adhikari
Jianlin Cheng
Homepage http://iris.rnet.missouri.edu/DeepSF/