Human Gene Catalogue ??, Microbiome Data Sharing Issues ??, Long-Read RNA-Seq Tool Benchmarks ??
Bioinformer Weekly Roundup
Stay Updated with the Latest in Bioinformatics!
Issue: 10 | Date: 6 October 2023
?? Welcome to the Bioinformer Weekly Roundup!
In this newsletter, we curate and bring you the most captivating stories, developments, and breakthroughs from the world of bioinformatics. Whether you're a seasoned researcher, a student, or simply curious about the intersection of biology and data science, we've got you covered. Subscribe now to stay ahead in the exciting realm of bioinformatics!
?? Featured Research
The article presents a benchmark experiment to compare tools for detecting long-read isoforms and analyzing differential gene expression. The study found that StringTie2 and bambu were the best for isoform detection, while DESeq2, edgeR, and limma-voom performed well for differential transcript expression; however, no tool stood out for analyzing differential transcript usage, suggesting more work is needed in that area.
The article introduces a new technology called single-cell Deep Visual Proteomics (scDVP) that combines imaging, laser microdissection, and mass spectrometry to study proteins in individual cells within tissues. The method was tested on mouse liver cells and could map out 1,700 proteins, showing that many proteins change levels based on their location in the tissue; it also used machine learning to predict these spatial changes.
The article introduces Genome Archive (GenArk), a collection of UCSC Genome Browsers that includes recent genome assemblies from the NCBI. GenArk allows for fast visualization of gene annotations and other genomic features, and it currently lists 3,269 assemblies that users can search and add annotations to.
??? Latest Tools
The researchers have created a tool called CellOT that uses two techniques: optimal transport and input convex neural networks. This tool can predict how individual cells will react to different changes or treatments. Compared to existing methods, CellOT is more accurate. It can even make good predictions for cell types and patients that it hasn't seen before.
The article discusses a new method called guided sparse factor analysis (GSFA) for analyzing data from single-cell CRISPR experiments. GSFA is more accurate at identifying how changes to genes affect cell behavior, compared to existing methods, and it has been tested on human T cells and neural progenitor cells to uncover new insights into immune response and brain development.
The article introduces iMVP, a new framework for analyzing epitranscriptomic data, which is data about RNA modifications. iMVP improves the identification of RNA modification sites and types, helps filter out false positives, and allows for the comparison of different data analysis methods, making it a valuable tool for better understanding RNA modifications.
?? Community News
The article reviews progress in identifying all the genes in the human genome, including protein-coding genes and non-coding RNA genes. It highlights the need for a universal standard for gene annotation, especially for medical applications, and discusses recent technological advances that help in understanding the function of newly discovered genes.
The article discusses the challenges and opportunities in sharing data in microbiome research, a field that deals with complex and large volumes of data. It emphasizes the need for best practices in data sharing and calls for incentives from institutions, journals, and funders to encourage proper data curation and dissemination.
Ewan Birney, the Deputy Director General of the European Molecular Biology Laboratory (EMBL), has authored a blog post highlighting EMBL's notable advancements in the fields of artificial intelligence and computational biology.
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?? Educational Corner
This is CS50's latest course on Introduction to Databases with SQL, led by CS50's very own Carter Zenke. You can enroll for free on edX.
The article offers a comprehensive tutorial on various methods used in "shotgun" or "bottom-up" proteomics, which involves breaking down proteins into peptides and analyzing them using mass spectrometry. Aimed at newcomers, the tutorial covers the entire workflow from protein extraction to interpreting the results, and it's intended to serve as a basic guide to this complex field.
In this month's bioinformatics blog from Genomics England, Genomic Data Scientists Kevin Savage and Mark Doherty discuss how new methods of detecting short-tandem repeats could bring genetic diagnoses to patients.
The blog by Valentine Svensson explains how to use the scVI model to analyze gene expression in single cells. The model is tested on data from 18 donors. It focuses on two genes, MS4A1 and TGFB1, and finds expression varies more by donor than health condition. To compare across donors, the model "adjusts" gene expression levels. This helps identify specific cell types like immune cells.
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