Publications by authors named "C Soneson"
Article Synopsis
- The study introduces qPISA, a new method for quantitatively analyzing protease specificity, particularly focusing on Dipeptidyl Peptidase Four (DPP4), which regulates blood glucose levels.
- Utilizing mass spectrometry, researchers quantified over 40,000 peptides, allowing for a deeper understanding of DPP4’s activity and revealing cooperative interactions within its active site.
- qPISA also distinguishes DPP4 from a similar enzyme in C. elegans and demonstrates potential applications in protein engineering, such as stabilizing GLP-1 for diabetes and obesity treatment.
Although transcriptomics data is typically used to analyze mature spliced mRNA, recent attention has focused on jointly investigating spliced and unspliced (or precursor-) mRNA, which can be used to study gene regulation and changes in gene expression production. Nonetheless, most methods for spliced/unspliced inference (such as RNA velocity tools) focus on individual samples, and rarely allow comparisons between groups of samples (e.g.
View Article and Find Full Text PDFArticle Synopsis
- The rise of omic data brings new challenges in how we handle, analyze, and integrate this information, which is crucial for biological research.
- Bioconductor serves as a comprehensive platform for community-driven analysis of biological data, while tidy R programming introduces an innovative approach for organizing and manipulating data.
- The tidyomics software ecosystem connects Bioconductor with tidy R practices, aiming to simplify omic analysis and facilitate collaboration across different scientific disciplines, as evidenced by its successful application in analyzing a large dataset from the Human Cell Atlas.
Article Synopsis
- - The increasing amount of omic data creates challenges in how to manage, analyze, and integrate this information.
- - Bioconductor offers a community-driven platform for biological data analysis, while tidy R programming introduces a new standard for organizing and manipulating data.
- - This software ecosystem connects Bioconductor with tidy R, aiming to simplify omic analysis and foster collaborations, demonstrated through the analysis of 7.5 million cells from the Human Cell Atlas.