2026-07-07T08:47:49Z https://api.figshare.com/v2/oai
oai:figshare.com:article/14979990 2021-07-22T11:00:58Z category_24208 portal_549 item_type_3 month_year_07_2021
10.5522/04/14979990.v3 https://figshare.com/articles/dataset/Protein_structures_predicted_using_DMPfold2/14979990 https://ndownloader.figshare.com/files/28839921 https://ndownloader.figshare.com/files/28839924 https://ndownloader.figshare.com/files/28839930 https://ndownloader.figshare.com/files/28839933 https://ndownloader.figshare.com/files/28839936 https://ndownloader.figshare.com/files/28912617 https://ndownloader.figshare.com/files/28912623 https://ndownloader.figshare.com/files/31185027 https://ndownloader.figshare.com/files/33897233 https://doi.org/10.1073/pnas.2113348119 10.1073/pnas.2113348119 Kandathil, Shaun Shaun Kandathil 0000-0002-2671-2140 Lau, Andy Andy Lau Greener, Joe Joe Greener Jones, David David Jones <![CDATA[Protein structures predicted using DMPfold2, plus training data]]> Bioinformatics and computational biology not elsewhere classified DMPfold2 Deep Learning Applications BFD Protein Structure Prediction End-to-end Deep Learning Bioinformatics Computational Biology 2022-01-27 2023-05-31 Dataset 2021 University College London
BFD_1.3M.hdf5 contains all the models from the set of 1.3M that were generated. The models can be retrieved from this file using the provided hdf5_extract.py script and the list of IDs in bfdfold_1.3M_target_ids.csv.

Also provided are tarballs of the models and sequence alignments for the 5193 Pfam families modelled in the paper, as well as for the set of 255 Pfams with released structures used for comparisons against DMPfold1 and C-I-TASSER.

train_data.tar.bz2 contains the data used to train the DMPfold2 neural network. Further scripts and instructions are available on the associated GitHub page: https://github.com/psipred/DMPfold2

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