ArticleScientific data2024
Multi-proteomics and interactome dataset of tick-borne encephalitis virus infected host cells.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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Who cites it
4 citing papers in PubMed.
- Nuclear activities and interactome of the NS5 protein of tick-borne encephalitis virus.Journal of virology · 2026Article
- Virus-host interactome reveals host cellular pathways perturbed by tick-borne encephalitis virus infection.iScience · 2026Article
- Spatially and temporally comparative proteomics provide insights into dynamic response patterns to PEDV infection.Communications biology · 2026Article
- Nuclear activities and interactome of the NS5 protein of Tick-Borne Encephalitis Virus.bioRxiv : the preprint server for biology · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tick-borne encephalitis virus (TBEV) is a significant viral pathogen transmitted by ticks, causing severe neurological complications in humans across Europe and Asia, highlighting the urgent need for an in-depth understanding of molecular functions of viral proteins and their interactions with the host proteome. Multi-omics analysis of how TBEV hijack cellular processes provides information about their replication and pathogenic mechanisms. Here, we focused on the proteome, phosphoproteome, and acetylproteome of Vero cells infected by TBEV, revealing the host perturbations triggered by TBEV infection. Additionally, we performed protein-protein interactome analysis to examine the interactions between TBEV and the host. We have provided technical validation, demonstrating the high quality and correlation of samples across all datasets, and evidence of biological consistency of virus-infected cells at the proteomic, phosphoproteomics and acetylomic levels. This comprehensive multi-omics dataset serves as a valuable resource for studying TBEV pathogenesis and identifying potential drug targets for TBEV therapy.
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Registered trials
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