🧬🖥 Protein Dimension DB 🖥🧬

Datasets with PLM embeddings, GO annotations and taxonomy 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
uniprot_sorted.fasta.gz	Aminoacid sequences of SwissProt proteins	UFRN
taxid.tsv	NCBI taxon ID of each protein	UFRN

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
go.experimental.mf.tsv.gz	Molecular Functions	UFRN
go.experimental.bp.tsv.gz	Biological Processes	UFRN
go.experimental.cc.tsv.gz	Cellular Components	UFRN

Protein Language Model 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
emb.ankh_large.npy	ankh-large	1536	Upcoming
emb.ankh_base.npy	ankh-base	768	Upcoming
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	UFRN
emb.esm2_t6.npy.gz	esm2_t6_8M_UR50D	320	UFRN

Taxonomy 🔢

Numerical representations of the NCBI taxon IDs of each protein. Instead of the original NCBI taxonomy tree, we use the custom taxonomy created by taxallnomy project, because it attributes the same number of parent taxa (genus, family, order...) to each species ID.

Name	Description	Vector Length 📏	Download Links 🔗
emb.taxa_profile_256.npy.gz	Taxa Proximity [0.0, 1.0] to each one of the 256 most annotated taxa	256	UFRN
emb.taxa_profile_128.npy.gz	Taxa Proximity [0.0, 1.0] to each one of the 128 most annotated taxa	128	UFRN
onehot.taxa_256.npy.gz	Taxa One-Hot Encoding	256	UFRN
onehot.taxa_128.npy.gz	Taxa One-Hot Encoding	128	UFRN

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 to generate the datasets from scratch:

• Nextflow >= 24
• Mamba package manager
• Fast and stable internet connection to download original datasets
• At least 16GB of RAM

$ nextflow run prepare_requirements.nf
$ nextflow run new_release.nf --release_dir <path to generate database at>