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nf-core/proteinfamilies: A scalable pipeline for the generation of protein families
Open accessPreprint — published as 10.1093/gigascience/giag009 · Paper page
Abstract
The growth of metagenomics-derived amino acid sequence data has transformed our understanding of protein function, microbial diversity and evolutionary relationships. However, the vast majority of these proteins remain functionally uncharacterized. Grouping the millions of such uncharacterised sequences with the few experimentally characterised ones allows the transfer of annotations, while the inspection of conserved residues with multiple sequence alignments can provide clues to function, even in the absence of existing functional information. To address the challenges associated with this data surge and the need to group sequences, we present a scalable, open-source, parametrizable Nextflow pipeline ( nf-core/proteinfamilies ) that generates protein nascent families or assigns new proteins to existing families. The computational benchmarks demonstrated that resource usage can scale approximately linearly with input size, while the biological benchmarks showed that the generated protein families closely resemble manually curated families found in widely used databases.
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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
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Metadata
- Authors
- Karatzas, E., Beracochea, M., Baltoumas, F. A., Aplakidou, E., Richardson, L., Fellows Yates, J. A., Lundin, D., community, N.-C., Buluç, A., Kyrpides, N. C., Georgakopoulos-Soares, I., Pavlopoulos, G. A., & Finn, R. D.
- Affiliations
- European Bioinformatics Institute (GB)
- Alexander Fleming Biomedical Sciences Research Center (GR)
- University of Crete (GR)
- Stockholm University (SE)
- Lawrence Berkeley National Laboratory (US)
- Mohamed bin Zayed University of Artificial Intelligence (AE)
- Corresponding author
- Finn, Robert D.
- ORCID
- Venue
- GigaScience
- Publisher
- openRxiv
- Published
- 2025-08-16
- Volume
- 15
- ISSN
- 2047-217X (ISSN-L)
- OpenAlex
- W7125234690
- Cited by
- 0
- References
- 1
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- GigaScience (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- MPG.PuRe (Max Planck Society) (submittedVersion, cc-by)
- DiVA (Linnaeus University) (submittedVersion, other-oa)
- Funders
- U.S. Department of Energy (-AC02-05CH11231, 05CH11231, 23592, DE AC02 05CH11231, DE-AC02-)
- University of Pennsylvania
- Pennsylvania State University (DE-AC02-05CH11231)
- Joint Genome Institute (AC02-05CH11231, DE–AC02–05CH11231)
- European Commission (HORIZON2020, DE-AC02-05CH11231, 945405)
- Hellenic Foundation for Research and Innovation (23592, 28787-VIROMINE, 23592-EMISSION, DE-AC02-05CH11231, 28787)
- Office of Science (https://ror.org/04xm1d337, DEAC02–05CH11231, AC02-05CH11231, DE-AC02, 05CH11231)
- Penn State College of Medicine
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- protein families, metagenomics, hypothetical protein, protein annotation, multiple sequence alignment, conserved residues, Nextflow pipeline, protein family clustering
- MeSH terms
- Algorithms, Amino Acid Sequence, Proteins, Software, Sequence Alignment, Computational Biology, Databases, Protein, Metagenomics, Molecular Sequence Annotation
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