Ling-Yi

Schedule – Applied Systems Biology Symposia Emmanuel Saliba, University of Würzburg, Germany.

Excited to present work from my preprint at #SMBI2025 @uni-jena.de on September 18th. I will be speaking on how spatial structure can explain the association of microbial accessory genes with inducible prophages.

asb-conference.hki-jena.de/schedule/

25.08.2025 18:17 — 👍 6    🔁 2    💬 0    📌 0

SpeSpeNet: an interactive and user-friendly tool to create and explore microbial correlation networks Abstract. Correlation networks are commonly used to explore microbiome data. In these networks, nodes are taxa and edges represent correlations between the

📣 New, free webtool by the Snoek lab! Meet SpeSpeNet, an intuitive platform for automated network analysis of microbiomes to uncover complex interactions between microbes and their environments

@ismepublications.bsky.social @isme-microbes.bsky.social
doi.org/10.1093/isme...

#microsky #mevosky

14.03.2025 14:14 — 👍 11    🔁 9    💬 2    📌 0

Get a grasp of the chemistry of microbiomes! Check out Pilleriin Peets' preprint: she developed chemical characteristics vectors to reanalyze EMP's untargeted metabolomics data: www.biorxiv.org/content/10.1... with Aris Litos, Daniel Garza, Kai Dührkop, @jjjvanderhooft.bsky.social & Sebastian Böcker

27.01.2025 13:25 — 👍 10    🔁 3    💬 1    📌 0

We (with Clement Coclet, not on Bsky) had the chance to work on a broad "state of viromics" review. We tried to use this to give an overview of how the field changed over the last ~ 15 years, and also what we think are some of the major remaining challenges. Full-text access at -> rdcu.be/excHt

22.07.2025 15:06 — 👍 84    🔁 41    💬 2    📌 2

Examples of protein annotations across functional classification schemes. Yellow: hierarchical classification schemes, red: orthologous/homologous groups, and blue: methods using protein domain information. Protein structures were generated using the ColabFold Alphafold MMseqs2 interactive notebook (version 1.5.2) (57) and visualized using ChimeraX (58). (A) Functional labels associated with the glycogen synthase protein in Escherichia coli (UniprotKB P0A6U8). (B) Functional labels associated with Kehishuvirus sp. tikala major capsid protein (NCBI WEU69752.1).

New in @asm.org #MMBR Computational function prediction of bacteria and phage proteins. How to annotate your #phage and #bacteria genomes

by @susiegriggo.bsky.social @bedutilh.bsky.social @gbouras13.bsky.social and Bob

#phagesky #microsky

journals.asm.org/doi/epub/10....

22.08.2025 04:00 — 👍 51    🔁 27    💬 1    📌 0

GitHub - Yasas1994/Jaeger: Jaeger is a quick and precise pipeline for detecting phages in sequence assemblies. Jaeger is a quick and precise pipeline for detecting phages in sequence assemblies. - Yasas1994/Jaeger

Based on our results we are currently developing a new CNN tool with even more accurate predictions: github.com/Yasas1994/Ja... Stay tuned! (4/4)

25.04.2024 08:30 — 👍 2    🔁 0    💬 0    📌 0

PPR-Meta: a tool for identifying phages and plasmids from metagenomic fragments using deep learning AbstractBackground. Phages and plasmids are the major components of mobile genetic elements, and fragments from such elements generally co-exist with chrom

Tools' performance ranked similarly in different biomes. #MachineLearning 🤖 tools outperformed homology-based tools. #CNN tools performed the best. The best tool was PPR-Meta, which uses a CNN containing two paths—a “base path” and a “codon path”: academic.oup.com/gigascience/.... (3/4)

25.04.2024 08:30 — 👍 0    🔁 0    💬 0    📌 0

We used paired viral (TP) and microbial (TN) metagenomes from #Antarctic water 🇦🇶🌊, tomato soil 🍅🌱, and human gut 💩. Real-world data 1: has high complexity, 2: avoids training/testing overlap, and 3: is more realistic than cropping mock contigs from reference genomes. (2/4)

25.04.2024 08:29 — 👍 1    🔁 0    💬 0    📌 0

Benchmarking bioinformatic virus identification tools using real-world metagenomic data across biomes - Genome Biology 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 bioinfo...

#Viromics #VirusDiscovery 🦠 by #Metagenomics 🧬! We used real metagenomic data from diverse biomes to #benchmark state-of-the-art #bioinformatics virus identification tools: genomebiology.biomedcentral.com/articles/10.... @goncalopiedade.bsky.social @bedutilh.bsky.social 🧵 (1/4)

25.04.2024 08:29 — 👍 21    🔁 12    💬 3    📌 1