Scalable Proteomics ?? ChatGPT for Nextflow ?? Universal Cell Embeddings Model ?? Bioinformatics for Ukraine ????

Scalable Proteomics ?? ChatGPT for Nextflow ?? Universal Cell Embeddings Model ?? Bioinformatics for Ukraine ????

Bioinformer Weekly Roundup

Stay Updated with the Latest in Bioinformatics!

Issue: 15 | Date: 1 December 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

Universal Cell Embeddings: A Foundation Model for Cell Biology | bioRxiv

The Universal Cell Embedding (UCE) model, trained on extensive cell atlas data, provides a universal representation of cells across species and tissues, enabling insights into cell types and functions without additional training or data labeling. This model has successfully embedded 36 million cells from various species, revealing new biological insights and demonstrating emergent behaviors in cell classification and analysis.

?? The first author, Yanay Rosen, has posted a Twitter thread giving an overview of the model and its details.

High-throughput and scalable single cell proteomics identifies over 5000 proteins per cell | bioRxiv

This study presents major advancements in single-cell proteomics (SCP) using mass spectrometry (MS), significantly enhancing its application in cellular biology and biomedicine. The researchers developed a nearly lossless workflow from sample preparation to MS analysis, increasing protein identification in individual cells from about 2000 to over 5000.

?? The corresponding author, Jesper V Olsen, has posted a Twitter thread detailing the uniqueness of the methodology and presenting the results.

Interpretable Inflammation Landscape of Circulating Immune cells | bioRxiv

This study utilizes single-cell genomics to understand the complexities of inflammation in various diseases. By analyzing over 2 million peripheral blood mononuclear cells from 356 patients across 18 diseases, researchers created a comprehensive atlas of inflammation in circulating immune cells.

?? The first author, Laura Jiménez Gracia, has posted a Twitter thread describing the motivation and main findings of the research.

Spatial methods for microbiome–host interactions | Nature Biotechnology

New methods by the groups of Stefania Giacomello and Sanja Vickovic, address the challenge in microbiome research of studying spatial interactions among microbes and hosts. These methods, which map transcriptomic activities, unveil complex local interactions in the 'interactome' of hosts, bacteria, and fungi, potentially advancing the field significantly.

??? Latest Tools

Deep generative modeling of the human proteome reveals over a hundred novel genes involved in rare genetic disorders | medRxiv

popEVE, a deep generative model, combines evolutionary and population sequence data to rank genetic variants by severity, improving identification of causal mutations in genetic disease diagnosis. Offering a unified scale for variant impact, popEVE is particularly effective for rare single-patient disorders where traditional methods fall short.

?? The corresponding author, Jonathan Frazer, has posted a Twitter thread introducing popEVE and the main findings from the paper.

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues | Nature Communications

The study introduces three algorithms in the stLearn software to enhance spatial transcriptomics data analysis: pseudo-time-space (PSTS) for modeling dynamic tissue transcriptional states, a spatially-constrained permutation test (SCTP) for identifying interactive tissue regions, and a spatial graph-based imputation method (stSME) to correct technical noise.

Paired single-cell multi-omics data integration with Mowgli | Nature Communications

The Multi-Omics Wasserstein inteGrative anaLysIs (Mowgli) is a new method for integrating paired multi-omics data of any type and quantity, combining integrative Nonnegative Matrix Factorization with Optimal Transport to improve clustering performance and interpretability.

Cardinal v.3: a versatile open-source software for mass spectrometry imaging analysis | Nature Methods

Cardinal v.3 is an upgraded open-source software for mass spectrometry imaging analysis. It supports various imaging workflows, offering advanced data processing, statistical analyses, and efficient handling of large-scale multitissue experiments.

Epiregulon: Inference of single-cell transcription factor activity to dissect mechanisms of lineage plasticity and drug response | bioRxiv

Epiregulon is a new method that constructs gene regulatory networks (GRNs) using single-cell genetic data to accurately predict the activity of transcription factors (TFs) and transcriptional coregulators.

?? Community News

Bioinformatics For Ukraine | Scientists Without Borders

Bioinformatics For Ukraine supports Ukrainian students and researchers affected by war, offering scholarships, mentorship, and research opportunities in bioinformatics. The initiative seeks partners and encourages donations for a brighter future in Ukraine.

?? Upcoming Events

Prenomics: Learn the basics of command-line programming, Virtual | 6 - 7 December 2023

Prenomics offers an online workshop teaching command-line programming basics and bioinformatics to beginners, especially PhD students and researchers. The course, with 30 spots, covers file structure, cloud computing, shell commands, and script writing, and is free.

?? Educational Corner

nf-coreGPT: A custom GPT to help develop, debug and learn about nextflow and nf-core | ChatGPT

Florian Wünnemann created a custom GPT to help develop, debug and learn about nextflow and nf-core. You can access nf-core GPT if you have a ChatGPT subscription.

NEJM Illustrated Gallery | New England Journal of Medicine

The NEJM Illustrated Gallery offers visual explanations of complex medical terms, serving as an educational resource to demystify difficult concepts in medicine.

Median-ratio normalization for bulk RNA-seq data | Matthew N. Bernstein

Matthew Bernstein authored a blog explaining the median ratio normalization method in the DESeq2 Bioconductor package, detailing its underlying assumptions and walking through the algorithm's specifics.

Principles of Effective Data Visualization | Cell Patterns

The article highlights the importance of visuals in science communication and suggests sequential design principles to enhance their effectiveness, addressing scientists' common lack of training in this area.

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Disclaimer: The information provided in this newsletter is for educational and informational purposes only and does not constitute professional advice.

Editor: James Ashmore | Contact: [email protected]

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