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ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Preprocessed Datasets for Interactive Exploration of DPCfam and DPCstruct Protein Domain Classifications

Authors: Nyandu Kagarabi, Emmanuel; Saadat, Elaheh; Piomponi, Valerio;

Preprocessed Datasets for Interactive Exploration of DPCfam and DPCstruct Protein Domain Classifications

Abstract

This deposit provides all preprocessed input files required to deploy DPCexplorer (https://doi.org/10.5281/zenodo.20575268), a Django-based interactive portal for the exploration of protein domain classifications produced by the DPCfam and DPCstruct pipelines. The application will soon be accessible at https://dpcexplorer.areasciencepark.it/ and is fully reproducible from https://github.com/RitAreaSciencePark/dpc_fam_and_struct_webapp. Both DPCfam and DPCstruct apply the Density Peak Clustering (DPC) algorithm to automatically group millions of protein domains into evolutionary families called metaclusters: 81,384 sequence-based (DPCfam) and 28,246 structure-based (DPCstruct), without any manual curation. Despite being openly available on Zenodo, exploring these datasets directly requires parsing gigabyte-scale archives, including an 81 GB XML file for DPCfam, which presents a real technical barrier for most researchers. DPCexplorer removes that barrier by turning these static repositories into a searchable web application with paginated metadata tables, a 3D molecular viewer (PDBe-Molstar), and one-click downloads of per-metacluster biological files. The files in this deposit are cleaned, database-ready derivatives of the two original datasets: DPCfam (doi:10.5281/zenodo.6900559) and DPCstruct (doi:10.5281/zenodo.13334296). They were produced by a dedicated Python preprocessing pipeline run on the ORFEO HPC cluster; all notebooks and scripts are openly available in the linked GitHub repository. This deposit consists of four archives: dpcexplorer_csv.tar.gz (3.1 GB): PostgreSQL-ready CSV files for the 10 core database tables, covering DPC shared entities, DPCfam metacluster properties and seed sequences, AlphaFold representatives, DPCstruct metacluster properties and representative seed sequences, and CATH/SCOP structural annotations. dpcfam_mcid_seeds.tar.gz (1.7 GB): One FASTA file per DPCfam metacluster (81,384 files), covering both the Standard subset (size ≥ 50 seeds) and DPCfamB (25 ≤ size < 50 seeds). dpcstruct_mcid_pdbs.tar.gz (1.2 GB): One ZIP subfolder per DPCstruct metacluster (28,246 total), each containing the representative PDB structures loaded by the integrated 3D viewer. dpcstruct_mcid_seeds.tar.gz (6.9 MB): One FASTA file per DPCstruct metacluster (28,246 files), holding the sequences of the representative domains. This work was carried out during a Research Internship at the Laboratory of Data Engineering (LADE), Area Science Park, Trieste, Italy, as part of the MDMC Master's programme at SISSA, and was funded by the European Union - NextGenerationEU (NFFA-DI, cod. IR0000015 and EFC, cod. SSU2024-00002).

Keywords

Django, UniRef50, open data, Reproducibility of Results, protein domain classification, AlphaFold, bioinformatics, web application, FAIR data principles, density peak clustering, DPCfam, protein family, PostgreSQL, DPCexplorer, DPCstruct, Foldseek, Python

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citations
The total number of citations received by all articles of the researcher of interest.
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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Average