Evidence map›Paper›PMID 39838963›Full record

ArticleBriefings in bioinformatics2024

GOPhage: protein function annotation for bacteriophages by integrating the genomic context.

Jiaojiao Guan, Yongxin Ji, Cheng Peng, Wei Zou, Xubo Tang, Jiayu Shang, Yanni Sun

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Article
  5. Review
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  7. Article
  8. Review
  9. Computational function prediction of bacteria and phage proteins.Microbiology and molecular biology reviews : MMBR · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jiaojiao GuanDepartment of Electrical Engineering, City University of Hong Kong, 83 Tat Chee Ave, Kowloon Tong, Hong Kong (SAR), China.ORCID 0009-0005-9200-4862
Yongxin JiDepartment of Electrical Engineering, City University of Hong Kong, 83 Tat Chee Ave, Kowloon Tong, Hong Kong (SAR), China.ORCID 0000-0001-5974-4985
Cheng PengDepartment of Electrical Engineering, City University of Hong Kong, 83 Tat Chee Ave, Kowloon Tong, Hong Kong (SAR), China.ORCID 0000-0002-8566-0707
Wei ZouDepartment of Electrical Engineering, City University of Hong Kong, 83 Tat Chee Ave, Kowloon Tong, Hong Kong (SAR), China.ORCID 0000-0003-2559-2519
Xubo TangDepartment of Electrical Engineering, City University of Hong Kong, 83 Tat Chee Ave, Kowloon Tong, Hong Kong (SAR), China.
Jiayu ShangDepartment of Information Engineering, Chinese University of Hong Kong, Shatin, New Territories, Hong Kong (SAR), China.
Yanni SunDepartment of Electrical Engineering, City University of Hong Kong, 83 Tat Chee Ave, Kowloon Tong, Hong Kong (SAR), China.ORCID 0000-0003-1373-8023

Funding

City University of Hong Kong 11209823
6 · The paper itself

Abstract

Bacteriophages are viruses that target bacteria, playing a crucial role in microbial ecology. Phage proteins are important in understanding phage biology, such as virus infection, replication, and evolution. Although a large number of new phages have been identified via metagenomic sequencing, many of them have limited protein function annotation. Accurate function annotation of phage proteins presents several challenges, including their inherent diversity and the scarcity of annotated ones. Existing tools have yet to fully leverage the unique properties of phages in annotating protein functions. In this work, we propose a new protein function annotation tool for phages by leveraging the modular genomic structure of phage genomes. By employing embeddings from the latest protein foundation models and Transformer to capture contextual information between proteins in phage genomes, GOPhage surpasses state-of-the-art methods in annotating diverged proteins and proteins with uncommon functions by 6.78% and 13.05% improvement, respectively. GOPhage can annotate proteins lacking homology search results, which is critical for characterizing the rapidly accumulating phage genomes. We demonstrate the utility of GOPhage by identifying 688 potential holins in phages, which exhibit high structural conservation with known holins. The results show the potential of GOPhage to extend our understanding of newly discovered phages.

Indexed as

BacteriophagesGenome, ViralMolecular Sequence AnnotationViral ProteinsComputational BiologyGenomicsViral Proteinsbacteriophagesgenomic contextual informationprotein function annotationprotein large language model

Identifiers

PMID39838963
PMCPMC11751364

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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.