ArticleGigaScience2022
3D-Beacons: decreasing the gap between protein sequences and structures through a federated network of protein structure data resources.
Article in GigaScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- 3DSeqCheck: A Web-based Tool for Verifying Sequence Consistency Between a 3D Structure File and the Corresponding UniProt Entry.Journal of molecular biology · 2026Article
- Effects of a cancer-associated mutation and multiple serine phosphorylation on poly(ADP-ribose) polymerase 2.Biophysical journal · 2026Article
- ModelCIF Update: Supporting Emerging Classes of Computational Macromolecular Models.Journal of molecular biology · 2026Article
- MolViewStories: Interactive molecular storytelling.Protein science : a publication of the Protein Society · 2026Article
- The Reactome Knowledgebase 2026.Nucleic acids research · 2026Article
- StoPred: Accurate Stoichiometry Prediction for Protein Complexes Using Protein Language Models and Graph Attention.Research square · 2025Article
- StoPred: Accurate Stoichiometry Prediction for Protein Complexes Using Protein Language Models and Graph Attention.bioRxiv : the preprint server for biology · 2025Article
- Ten rules for a structural bioinformatic analysis.PLoS computational biology · 2025Article
- ModelArchive: A Deposition Database for Computational Macromolecular Structural Models.Journal of molecular biology · 2025Article
- Archaeal hemeFrontiers in microbiology · 2025Article
- Exploring Shootin1's oncogenic role withinTurkish journal of biology = Turk biyoloji dergisi · 2025Article
- Challenges in bridging the gap between protein structure prediction and functional interpretation.Proteins · 2025Article
- MgJACS Au · 2024Article
- Dataset from a human-in-the-loop approach to identify functionally important protein residues from literature.Scientific data · 2024Article
- EMBL's European Bioinformatics Institute (EMBL-EBI) in 2023.Nucleic acids research · 2024Review
- PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins.Nucleic acids research · 2024Article
- ModelCIF: An Extension of PDBx/mmCIF Data Representation for Computed Structure Models.Journal of molecular biology · 2023Article
- FuzPred: a web server for the sequence-based prediction of the context-dependent binding modes of proteins.Nucleic acids research · 2023Article
- 3D-Beacons: decreasing the gap between protein sequences and structures through a federated network of protein structure data resources.GigaScience · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
32 authors.
Funding
Abstract
While scientists can often infer the biological function of proteins from their 3-dimensional quaternary structures, the gap between the number of known protein sequences and their experimentally determined structures keeps increasing. A potential solution to this problem is presented by ever more sophisticated computational protein modeling approaches. While often powerful on their own, most methods have strengths and weaknesses. Therefore, it benefits researchers to examine models from various model providers and perform comparative analysis to identify what models can best address their specific use cases. To make data from a large array of model providers more easily accessible to the broader scientific community, we established 3D-Beacons, a collaborative initiative to create a federated network with unified data access mechanisms. The 3D-Beacons Network allows researchers to collate coordinate files and metadata for experimentally determined and theoretical protein models from state-of-the-art and specialist model providers and also from the Protein Data Bank.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.