our new NAR paper is out: "WikiPathways 2024: next generation pathway database" doi.org/10.1093/nar/gkad960

April 2024 WikiPathways release: 290 edits by 11 contributors and 2 new pathways. Accessible via #webservices and in PathVisio, Cytoscape. Supported by AWSOpen. wikipathways.org/#download #bioinformatics #openscience #opensource

**We are moving platforms**

Bioconductor will cease posting on Twitter/X as of December 17, 2023. Instead we will be continuing to post on other social media platforms that better reflect our community’s code of conduct.

Check out our blog post which explains our decision: blog.bioconductor.org/posts/20

Note to my health provider's 24 medical advice line: "Knocking on Heaven's Door" slaps but maybe isn't the best hold music for y'all.

Do any Mastodon clients sort your home feed by engagement? Or allow customization of the home feed?

Wikipedia is now on Mastodon, at @wikipedia!

They've taken an interesting approach here, as it is an account run by the community, where everyone can contribute (explanation here: meta.wikimedia.org/wiki/@Wikip). At the same time, it is verified on the official homepage of wikipedia.org, as you can see in the screenshot.

Personally, I think this suits the spirit of the fediverse that the Wikipedia account is not a PR department, but community members building something together!

Recommended Long Now Talk: A great conversation between Annalee Newitz @annaleen and Becky Chambers at The Interval in SF. Resisting Dystopia: youtube.com/live/XI6qAIJbjs0?f

Change is coming to WikiPathways! Keep an eye out for major enhancements in the coming months. Early next week we will be switching wikipathways.org/ to the new site. Preview at new.wikipathways.org/ and learn more at our new discussion forum: github.com/wikipathways/wikipa

Single-Cell ATAC-seq analysis via Network Refinement with peaks location information biorxiv.org/content/10.1101/20

Single-Cell ATAC-seq analysis via Network Refinement with peaks location information

Single-cell ATAC-seq (scATAC-seq) data provided new insights into the elaboration of cellular heterogeneity and transcriptional regulation. However, scATAC-seq data posed challenges for data analysis because of its near binarization, high sparsity, and ultra-high dimensionality properties. Here we proposed a novel network diffusion-based method to comprehensively analyze scATAC-seq data, named Single-Cell ATAC-seq Analysis via Network Refinement with Peaks Location Information (SCARP). By modeling the prior probability of co-accessibility between adjacent peaks as a decreasing function of genomic distance, SCARP is the first scATAC-seq analysis method that utilizes the genomic information of peaks, which contributed to characterizing co-accessibility of peaks. SCARP used network to model the accessible relationships between cells and peaks, aggregated information with the diffusion method, and then performed dimensionality reduction to obtain low-dimensional cell embeddings as well as peak embeddings. We have demonstrated through sufficient experiments that SCARP facilitated superior analysis of scATAC-seq data. Specifically, SCARP exhibited outstanding cell clustering performance to better elucidate cell heterogeneity, and can be used to reveal new biologically significant cell subpopulations. SCARP was also instrumental in portraying co-accessibility relationships of accessible regions and providing new insight into transcriptional regulation, and those SCARP-derived genes were involved in some key KEGG pathways related to diseases. To sum up, our studies suggested that SCARP is a promising tool to comprehensively analyze the scATAC-seq data from a new perspective. ### Competing Interest Statement The authors have declared no competing interest.

www.biorxiv.org

Hi all, WikiPathways is now also on Mastodon: @wikipathways
WikiPathways is an open, public platform dedicated to the collection and curation of biological pathways by and for the scientific community #introduction

@kensanata Please add me to Academia, Biology, Java, Javascript, Machine Learning & Artificial Intelligence, Open Education, Programming, Python, Science, Systems Thinking, Wiki.

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