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Mitochondrial DNA is a target of HBV integration
Hepatitis B virus (HBV) may integrate into the genome of infected cells and contribute to hepatocarcinogenesis. However, the role of HBV integration...
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Characterizing the impacts of dataset imbalance on single-cell data integration
Computational methods for integrating single-cell transcriptomic data from multiple samples and conditions do not generally account for imbalances in...
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Web-based multi-omics integration using the Analyst software suite
The growing number of multi-omics studies demands clear conceptual workflows coupled with easy-to-use software tools to facilitate data analysis and...
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Genomic data integration tutorial, a plant case study
BackgroundThe ongoing evolution of the Next Generation Sequencing (NGS) technologies has led to the production of genomic data on a massive scale....
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Human papillomavirus integration transforms chromatin to drive oncogenesis
BackgroundHuman papillomavirus (HPV) drives almost all cervical cancers and up to 70% of head and neck cancers. Frequent integration into the host...
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Stabilized mosaic single-cell data integration using unshared features
Currently available single-cell omics technologies capture many unique features with different biological information content. Data integration aims...
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Mosaic integration and knowledge transfer of single-cell multimodal data with MIDAS
Integrating single-cell datasets produced by multiple omics technologies is essential for defining cellular heterogeneity. Mosaic integration, in...
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Coexpression enhances cross-species integration of single-cell RNA sequencing across diverse plant species
Single-cell RNA sequencing is increasingly used to investigate cross-species differences driven by gene expression and cell-type composition in...
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High-efficiency targeted transgene integration via primed micro-homologues
Due to the difficulties in precisely manipulating DNA repair pathways, high-fidelity targeted integration of large transgenes triggered by...
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Orthogonal multimodality integration and clustering in single-cell data
Multimodal integration combines information from different sources or modalities to gain a more comprehensive understanding of a phenomenon. The...
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Population-level integration of single-cell datasets enables multi-scale analysis across samples
The increasing generation of population-level single-cell atlases has the potential to link sample metadata with cellular data. Constructing such...
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Integration of spatial and single-cell data across modalities with weakly linked features
Although single-cell and spatial sequencing methods enable simultaneous measurement of more than one biological modality, no technology can capture...
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Efficient and markerless gene integration with SlugCas9-HF in Kluyveromyces marxianus
The nonconventional yeast Kluyveromyces marxianus has potential for industrial production, but the lack of advanced synthetic biology tools for...
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ViroISDC: a method for calling integration sites of hepatitis B virus based on feature encoding
BackgroundHepatitis B virus (HBV) integrates into human chromosomes and can lead to genomic instability and hepatocarcinogenesis. Current tools for...
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Factors influencing gender and youth integration in agricultural research and innovation in Africa
Integrating gender and youth in Agricultural Research and Innovation (R & I) is important for strengthening the impact and inclusiveness of the...
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MASI enables fast model-free standardization and integration of single-cell transcriptomics data
Single-cell transcriptomics datasets from the same anatomical sites generated by different research labs are becoming increasingly common. However,...
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Dynamic evolutionary interplay between ontogenetic skull patterning and whole-head integration
The arrangement and morphology of the vertebrate skull reflect functional and ecological demands, making it a highly adaptable structure. However,...
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BIONIC: biological network integration using convolutions
Biological networks constructed from varied data can be used to map cellular function, but each data type has limitations. Network integration...
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Domain adaptation for supervised integration of scRNA-seq data
Large-scale scRNA-seq studies typically generate data in batches, which often induce nontrivial batch effects that need to be corrected. Given the...
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Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials
Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack...
