ArticleNucleic acids research2026
ViMIC 2.0: an updated database of human disease-related viral mutations, integration sites, and multi-omics data.
Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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
1 citing paper in PubMed.
- The 2026 Nucleic Acids Research database issue and the online molecular biology database collection.Nucleic acids research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
ViMIC 2.0 is an updated database that provides comprehensively curated data on virus mutations (VMs), viral integration sites (VISs), and multi-omics datasets related to human diseases. Leveraging expanding public data, ViMIC 2.0 significantly enhanced data scale, diversity, and analytical capabilities compared to the previous version. In terms of data volume, the number of virus types has increased from 8 to 28, VM entries have grown from 31 712 to 64 168, virus-related diseases expanded from 77 to 177, literature rose from 2539 to 6433, and omics datasets have substantially increased from 28 sets of single expression profile data to 255 sets of multi-omics data. In addition, ViMIC 2.0 has updated 9409 VISs, 173 048 sequences, newly incorporated sequencing types such as single-cell transcriptomic sequencing (scRNA-seq), and genome binding/occupancy profiling. Regarding the visualization module, ViMIC 2.0 now provides results of differential gene expression analysis for bulk RNA-seq or array, cell type annotation and gene feature plot for scRNA-seq data, and differential methylation analysis for methylation profiling, as well as peak annotation for ChIP-seq/ChIP-on-chip/ATAC-seq data. In summary, ViMIC 2.0 serves as a user-friendly, up-to-date, and well-maintained resource for the virology research community. ViMIC 2.0 is freely accessible at http://www.biomedinfo.cn/ViMIC2.0/index.php.
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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.