ArticleGigaScience2022
DeePVP: Identification and classification of phage virion proteins using deep learning.
Article in GigaScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- Precision phage therapy in the AI/ML era: a systematic review of discovery-to-clinical translation evidence.Frontiers in microbiology · 2026Pooled it
- Phage therapy with nebulized cocktail BX004-A for chronic Pseudomonas aeruginosa infections in cystic fibrosis: a randomized first-in-human trial.Nature communications · 2025Trial
- ViralMap: predicting features in viral proteins from primary sequence.Journal of virology · 2026Article
- Artificial Intelligence in Bacteriophage Science: A Comprehensive Narrative Review of Applications, Challenges, and Translational Opportunities.Antibiotics (Basel, Switzerland) · 2026Review
- EAGP: an efficient generative augmentation framework for phage protein classification under severe class imbalance.Bioinformatics (Oxford, England) · 2026Article
- Phage Frontiers: Genomic and Functional Profiling of Novel Virulent Agents Targeting FoodborneBiology · 2026Article
- Review
- Empathi: embedding-based phage protein annotation tool by hierarchical assignment.Nature communications · 2025Article
- Fold first, ask later: structure-informed function annotation ofbioRxiv : the preprint server for biology · 2025Article
- ProtPhage: a deep learning framework for phage viral protein identification and functional annotation.Briefings in bioinformatics · 2025Article
- Optimizing phage therapy with artificial intelligence: a perspective.Frontiers in cellular and infection microbiology · 2025Review
- Exploring protein natural diversity in environmental microbiomes with DeepMetagenome.Cell reports methods · 2024Article
- Isolation and Characterization of a NovelAntibiotics (Basel, Switzerland) · 2024Article
- Article
- Large language models improve annotation of prokaryotic viral proteins.Nature microbiology · 2024Article
- metaProbiotics: a tool for mining probiotic from metagenomic binning data based on a language model.Briefings in bioinformatics · 2024Article
- MOBFinder: a tool for mobilization typing of plasmid metagenomic fragments based on a language model.GigaScience · 2024Article
- PhageScanner: a reconfigurable machine learning framework for bacteriophage genomic and metagenomic feature annotation.Frontiers in microbiology · 2024Article
- Knowing and Naming: Phage Annotation and Nomenclature for Phage Therapy.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Review
- Identification of plant vacuole proteins by using graph neural network and contact maps.BMC bioinformatics · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMany biological properties of phages are determined by phage virion proteins (PVPs), and the poor annotation of PVPs is a bottleneck for many areas of viral research, such as viral phylogenetic analysis, viral host identification, and antibacterial drug design. Because of the high diversity of PVP sequences, the PVP annotation of a phage genome remains a particularly challenging bioinformatic task.
findingsBased on deep learning, we developed DeePVP. The main module of DeePVP aims to discriminate PVPs from non-PVPs within a phage genome, while the extended module of DeePVP can further classify predicted PVPs into the 10 major classes of PVPs. Compared with the present state-of-the-art tools, the main module of DeePVP performs better, with a 9.05% higher F1-score in the PVP identification task. Moreover, the overall accuracy of the extended module of DeePVP in the PVP classification task is approximately 3.72% higher than that of PhANNs. Two application cases show that the predictions of DeePVP are more reliable and can better reveal the compact PVP-enriched region than the current state-of-the-art tools. Particularly, in the Escherichia phage phiEC1 genome, a novel PVP-enriched region that is conserved in many other Escherichia phage genomes was identified, indicating that DeePVP will be a useful tool for the analysis of phage genomic structures.
conclusionsDeePVP outperforms state-of-the-art tools. The program is optimized in both a virtual machine with graphical user interface and a docker so that the tool can be easily run by noncomputer professionals. DeePVP is freely available at https://github.com/fangzcbio/DeePVP/.
Indexed as
Identifiers
What Socratic 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 Socratic graph.