Do you perform analysis on #metagenomics, #metataxonomics #metatranscriptomics #metaproteomics datasets?
Would you like to find out how to make your #bioinformatic analysis more efficient, scalable, and reproducible?
Join us on December 10th for an online ‘Meta-*omics #Nextflow #pipeline community exhibition day’, for an intro and hands-on tutorial directly from the developers!
Interested? Please register your interest with this link: https://tally.so/r/31qJyQ !
Google Deepmind: "AlphaGenome: #AI for better understanding the #genome"
https://deepmind.google/discover/blog/alphagenome-ai-for-better-understanding-the-genome/
🟣Health Data Science Day 2025🟣
🥁KEYNOTE REVEAL: Naomi Wray!
She directs the Pioneer Centre for #SMARTbiomed, a Denmark-Oxford collaboration. Her research focuses on developing analytical methods for understanding common complex diseases, especially psychiatric disorders.
🗓️ 6 Nov 2025
📍 Panum, University of Copenhagen
👥 Open to all in Health Data Science
🌍 https://heads.ku.dk/calendar/2025/events/hdsd2025/
#healthdatascience
#machinelearning #deeplearning #clinicaldecisionmaking #hdsd #conference #bioinformatic
Seems like gmap does this sort of thing and will output into a gff3 format 👍 It was published in 2005 - goes to show that #bioinformatic tools don’t always need to be replaced with new tools.
https://academic.oup.com/bioinformatics/article/21/9/1859/409207
Metabarcoding, metagenomics and other omics methods revolutionize the study and monitoring of aquatic ecosystems. Come and join the 350 scientists and managers who will be discussing the use and development of these methods.
https://aquaecomics.symposium.inrae.fr/
#metabarcoding #metagenomics #fish #algae #protist #DNA #bioinformatic #pipeline #omics #MolecularEcology
Benchmarking #bioinformatic #virus identification tools using real-world #metagenomic data across biomes
https://genomebiology.biomedcentral.com/articles/10.1186/s13059-024-03236-4
Background As most viruses remain uncultivated, metagenomics is currently the main method for virus discovery. Detecting viruses in metagenomic data is not trivial. In the past few years, many bioinformatic virus identification tools have been developed for this task, making it challenging to choose the right tools, parameters, and cutoffs. As all these tools measure different biological signals, and use different algorithms and training and reference databases, it is imperative to conduct an independent benchmarking to give users objective guidance. Results We compare the performance of nine state-of-the-art virus identification tools in thirteen modes on eight paired viral and microbial datasets from three distinct biomes, including a new complex dataset from Antarctic coastal waters. The tools have highly variable true positive rates (0–97%) and false positive rates (0–30%). PPR-Meta best distinguishes viral from microbial contigs, followed by DeepVirFinder, VirSorter2, and VIBRANT. Different tools identify different subsets of the benchmarking data and all tools, except for Sourmash, find unique viral contigs. Performance of tools improved with adjusted parameter cutoffs, indicating that adjustment of parameter cutoffs before usage should be considered. Conclusions Together, our independent benchmarking facilitates selecting choices of bioinformatic virus identification tools and gives suggestions for parameter adjustments to viromics researchers.
We wonder if anyone is up for the challenge of figuring out how to repurpose the new NPU chips for simulating DNA structures and other interlinked bioinformatics simulation tasks instead of "AI" LLMs...
#dna #bioinformatics #bioinformatic #transhumanism #technology #tech #science #npu #simulation #freedomofform #opensource #gnugpl #gplv2 #biohacking
James Fellows Yates
Jesus Castagnetto 🇵🇪
Center for Health Data Science
Dave Tabb
Luke Pembleton
victorjavierlo
Lukas Brausch
AquaEcOmics
Frank Aylward
Vulpine Labs Inc.