karyoploteR is an R package that’s been in Bioconductor for nearly a decade. It lets you create linear chromosomal representations of any genome with genomic annotations and experimental data plotted along them. Bioconductor : https://bioconductor.org/packages/karyoploteR/ Tutorial : https://bernatgel.github.io/karyoploter_tutorial/ Paper : Bernat Gel & Eduard Serra. (2017).

Wir haben eine wichtige Änderung zu verkünden: Aus dem Open-Access-Büro Berlin wird das Open Research Office Berlin – Landeskoordinierungsstelle für offene Wissenschaft in Berlin. Die Umbenennung ist Teil eines größeren Prozesses, den wir in diesem Blogpost näher darstellen.

Introduction A major update to ggplot2 (version 4.0.0) is expected around mid-to-late July 2025 . It brings a significant internal change, replacing most of the S3 backend with the newer S7 object system. While this improves long-term maintainability and extensibility, it may break Bioconductor packages that depend on ggplot2, especially those that customise how plots are built or styled.

To address the growing scale and complexity of scholarly data, we’ve launched a new data science function at Crossref. In April, we were excited to welcome our first data scientists, Jason Portenoy and Alex Bédard-Vallée, to the team.

New US National Academy of Sciences Report reveals the complex web of societal vulnerabilities that could amplify nuclear war’s devastating impact TLDR/Summary The US National Academy of Sciences has just released a comprehensive report on the “Environmental Effects of Nuclear War”. This work extends analysis beyond physical damage to examine impacts on human social and economic systems.

When I read Andrej Karpathy’s endorsement of “context engineering” in a Twitter exchange with Shopify’s Tobi Lutke, I felt he tapped into something we all felt to some degree: tweet={"url":"https:\/\/twitter.com\/karpathy\/status\/1937902205765607626","author_name":"Andrej Karpathy","author_url":"https:\/\/twitter.com\/karpathy","html":"\u003Cblockquote class=\"twitter-tweet\" align=\"center\"\u003E\u003Cp lang=\"en\" dir=\"ltr\"\u003E+1 for

A recent report by the Dutch RIVM, PFAS in the blood of the Dutch population (doi:10.21945/RIVM-2025-0094), writes that seven PFAS compounds are found in blood samples of all tested people. Another nine compounds are found in at least 1-in-10 people. Because there is relevant data in the report on the 28 studied PFAS compound, I wanted to have the report more FAIR than it is on the website. Why this report?

Lateral ( a, b ) and postero-dorsal ( c ) views of the head and neck region in alcohol-preserved, intact specimens of Congosorex verheyeni ( a , SMNS 50411), Surdisorex norae ( b , FMNH 190260) and Congosorex phillipsorum ( c , FMNH 177721). Posterodorsal view ( c ) is of the same semi-transverse section, osteology in red, with

I’ve long been a proponent of making quantitative research reproducible. It’s the main reason I do all my scientific writing in Quarto—I can mix code and text in the same document so I don’t need to copy/paste numbers, tables, and figures from some statistical program into a word processor. Everything automatically ends up one compiled document based on the most current data.

(This was buried in Part 5 of my 2011 review of the Sideshow Apatosaurus maquette, but it’s long deserved to be a post of its own, and now it is. I’m not adding anything new here, just extracting and reposting the relevant bits, for reasons that will become clear in a future post.

My blog focuses on the two primary ways "AI"—or more accurately, transformer-based models—are impacting academic search.