ViMIC 2.0: an updated database of human disease-related viral mutations, integration sites, and multi-omics data

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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Publication Details

Journal
Nucleic Acids Research
Published
2025-10-08
DOI
https://doi.org/10.1093/nar/gkaf1106
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.81
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ViMIC 2.0: an updated database of human disease-related viral mutations, integration sites, and multi-omics data

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ViMIC 2.0: an updated database of human disease-related viral mutations, integration sites, and multi-omics data

Chenjun Huang, Zeyuan Zhang, Jiawen Zhu, Xiaoyan Zhang, M. James C. Crabbe, Honglian Huang, Min Wang, Ying Wang, Min Ding, Xiaoyang Zhao, Zhiqiang Wei, Xin Qin
article en
1 citations

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.

Nucleic Acids ResearchVol. 54(D1)
Tongji University (CN), University of Bedfordshire (GB), Second Military Medical University (CN), Shanxi University (CN), Renji Hospital (CN), University of Oxford (GB), Shanghai University of Traditional Chinese Medicine (CN), Yueyang Hospital (CN), Shanghai First People's Hospital (CN), Eastern Hepatobiliary Surgery Hospital (CN), PLA Navy General Hospital (CN)
Openalex Percentile: Top 22%
Single-cell and spatial transcriptomics
0.81
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