Comments (2)
Thank you for your interest in DeepAffinity. 'protein_sequence_SPS_mapping' Is prepared by ourself and used for the paper. It is for proteins in bindingdb so besides other species it is a subset for human proteome. ‘uniprot.human.scratch_outputs.w_sps.tab_corrected’ is kindly prepared by Dr. Tomas Babak at Queens University in 2021. It included all human proteome and was done after the publication.
We didn’t compare the two files to see whether they are consistent in the intersection. So thank you for the note! About your example, it appears that some secondary structure elements’ predicted overall secondary structure type or solvent exposure were not consistent, possibly due to different versions of SCRATCH for the corresponding prediction. Their source amino acid sequences in this case seem to be the same uniprot sequence though.
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Thank you so much!
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Related Issues (15)
- Data HOT 8
- model number in output
- Is the tool Mac compatible?
- Can't create environment
- Both Training and Testing with my own dataset.
- Typrerror when running joint-Model_test.py HOT 1
- Trained Models HOT 6
- Pubchem fingerprints HOT 2
- why tflearn? HOT 2
- Checkpoint for ki dataset HOT 2
- Generating the protein SPS representation HOT 12
- DeepAffinity ID and Public ID Mapping Table HOT 4
- No BindingDB_All.tsv exists. HOT 2
- Why should the number of SAP representation protein sequence file lines and the number of Canonical compound SMILE file lines match? HOT 2
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