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🧬🖥 Protein Dimension DB 🖥🧬

Datasets with embeddings and other representations for all proteins in Uniprot/Swiss-Prot

Current Release

Proteins are sorted by length. All files contain the same sequence of proteins, so the "ids.txt" file can be used as the row names.

Uniprot/Swiss-Prot 🔬

Name Content Download Links 🔗
ids.txt Uniprot Accession IDs UFRN, Zenodo
uniprot_sorted.fasta.gz Aminoacid sequences of SwissProt proteins UFRN, Zenodo
taxid.tsv NCBI taxon ID of each protein UFRN, Zenodo

Protein Annotations 📚

All Gene Ontology annotations of Swiss-Prot proteins, excluding computational, non-traceable and no-data annotations. The full list of ignored evidence codes is available at evi_not_to_use.txt. Annotations have been "expanded upwards": parent terms of existing annotations have been included in these files.

Name Content Download Links 🔗
go.expanded.tsv.gz MF, BP and CC annotations in simplified GAF format UFRN, Zenodo
go.experimental.mf.tsv.gz Molecular Functions UFRN, Zenodo
go.experimental.bp.tsv.gz Biological Processes UFRN, Zenodo
go.experimental.cc.tsv.gz Cellular Components UFRN, Zenodo

Embeddings 🔢

Several models are used to create computational descriptions of the Swiss-Prot proteins:

Name Model 🤖 Vector Length 📏 Download Links 🔗
emb.prottrans.npy.gz prottrans_t5_xl_u50 (calculated by Uniprot) 1024 UFRN, Zenodo
emb.esm2_t33.npy.gz esm2_t33_650M_UR50D 1280 Upcoming
emb.esm2_t30.npy.gz esm2_t30_150M_UR50D 640 Upcoming
emb.esm2_t12.npy.gz esm2_t12_35M_UR50D 480 Upcoming
emb.esm2_t6.npy.gz esm2_t6_8M_UR50D 320 Upcoming
emb.taxa_profile_256.npy.gz Taxa Profile v1 256 Upcoming
emb.taxa_profile_128.npy.gz Taxa Profile v1 128 Upcoming
onehot.taxa_128.npy.gz Taxa One-Hot Encoding 128 Upcoming

File Formats 🗃️

Files Format Descriptions
ids.txt One UniprotID per line
taxid.tsv Tab-separated table with columns: UniprotID, NCBI Taxon ID
go.expanded.tsv.gz Tab-separated table with columns: UniprotID, GO ID, ECO ID, NCBI Taxon ID, GO Ontology Code
go.experimental.*.tsv.gz Tab-separated table with columns: UniprotID, GO IDs separated by ','
emb.*.npy.gz Numpy matrix compressed with gzip. For rows where an embedding could not be defined, a vector of np.NaN is placed.

Create Release

Requirements:

  • Nextflow >= 24
  • Mamba package manager
  • Internet connection to download original datasets
$ nextflow run prepare_requirements.nf
$ nextflow run new_release.nf --release_dir <path to generate database at>