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Reposted by Sergey Nurk

Adam Phillippy @aphillippy.bsky.social · 6h

The T2T zebra finch genome has hatched! 🐣 🧬 @vertebrategenomes.bsky.social

bioRxiv Genomics @biorxiv-genomic.bsky.social · 13h

The complete genome of a songbird https://www.biorxiv.org/content/10.1101/2025.10.14.682431v1

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Ewan Birney @ewanbirney.bsky.social · 5d

I am hiring! - looking for a Staff Scientist to co-run my research group with me. Staff Scientist is a senior professional scientist role at EMBL. Please forward to people you might know who could be interested! embl.wd103.myworkdayjobs.com/en-US/EMBL/j...

Staff Scientist

About EMBL-EBI EMBL’s European Bioinformatics Institute is a data powerhouse, utilised on a global scale to advance scientific discovery through bioinformatics and solutions to some of the world’s mos...

embl.wd103.myworkdayjobs.com

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Rob Patro @robp.bsky.social · 6d

The Metagraph paper is out in Nature; it showed up in my feeds today! Congratulations to Mikhail Karasikov, @gxxxr.bsky.social, @akkah21.bsky.social and all of the other authors (whom I'd love to follow on Bluesky if I can find you ;P) www.nature.com/articles/s41...

Efficient and accurate search in petabase-scale sequence repositories - Nature

MetaGraph enables scalable indexing of large sets of DNA, RNA or protein sequences using annotated de Bruijn graphs.

www.nature.com

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Ben Langmead @benlangmead.bsky.social · 8d

I've added 7 videos to my Burrows-Wheeler indexing playlist (www.youtube.com/playlist?lis...), rounding out the r-index series and adding a 5-part series on the move structure. Now 27 videos in that playlist. I aim to add videos on prefix-free parsing, PBWT, Wheeler languages/automata in the future.

Burrows-Wheeler Indexing - YouTube

Videos on : (a) the Burrows-Wheeler Transform (BWT), (b) the FM Index, which uses the BWT to construct a full-text index, (c) Wheeler graphs, (d) r-index, an...

www.youtube.com

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Xian Chang @xian-chang.bsky.social · 13d

🦒Long read giraffe is out!🦒
Mapping long reads to pangenome graphs is ~10x faster than with GraphAligner, with veeery slightly better mapping accuracy, short variant calling, and SV genotyping than GraphAligner or Minimap2

bioRxiv Bioinfo @biorxiv-bioinfo.bsky.social · 13d

Rapid, accurate long- and short-read mapping to large pangenome graphs with vg Giraffe https://www.biorxiv.org/content/10.1101/2025.09.29.678807v1

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Heng Li @lh3lh3.bsky.social · 15d

Do you know ~60% of human SVs fall in ~1% of GRCh38? See our new preprint: arxiv.org/abs/2509.23057 and the companion blog post on how we started this project and longdust: lh3.github.io/2025/09/29/o.... Work with Alvin Qin

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Zamin Iqbal @zaminiqbal.bsky.social · 19d

Delighted to see our paper studying the evolution of plasmids over the last 100 years, now out! Years of work by Adrian Cazares, also Nick Thomson @sangerinstitute.bsky.social - this version much improved over the preprint. Final version should be open access, apols.
Thread 1/n

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Adam Phillippy @aphillippy.bsky.social · 23d

Delighted to finally announce a preprint describing the Q100 project! “A complete diploid human genome benchmark for personalized genomics” For which we finished HG002 to near-perfect accuracy: www.biorxiv.org/content/10.1... 🧵[1/14]

A complete diploid human genome benchmark for personalized genomics

Human genome resequencing typically involves mapping reads to a reference genome to call variants; however, this approach suffers from both technical and reference biases, leaving many duplicated and ...

www.biorxiv.org

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Sina Majidian @sinamajidian.bsky.social · 24d

Excited to share our EvANI benchmarking workflow, published in Briefings in Bioinformatics doi.org/10.1093/bib/...
Computing average nucleotide identity (ANI) is neither conceptually nor computationally trivial. Its definition has evolved over years, with different meanings and assumptions (1/5)

Figure 1(A) ANI quantifies the similarity between two genomes. ANI can be defined as the number of aligned positions where the two aligned bases are identical, divided by the total number of aligned bases. Historically, ANI was calculated using a single gene family for multiple sequence alignment. Another approach finds orthologous genes between two genomes and reports the average similarity between their CDSs. This method was later extended to whole-genome alignment by identifying local alignments and excluding supplementary alignments with lower similarity. (B) Different ANI tools employ various approaches in calculating ANI values. ANIm, OrthoANI, and FastANI use aligners to identify homologous regions, whereas Mash uses k-mer hashing to estimate similarities. Only alignments with higher similarity represented by green arrows are included in ANI calculations, while red arrows, corresponding to paralogs, are excluded. (C) The proposed benchmarking method evaluates the performance of different tools using both real and simulated data. It assumes that more distantly related species on the phylogenetic tree should have lower ANI similarities. This is measured by calculating the statistics of Spearman rank correlation. We expect a negative correlation between ANI and the tree distance (scatter plot on the right).
https://academic.oup.com/bib/article/doi/10.1093/bib/bbaf267/8160681

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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 24d

MMseqs2-GPU sets new standards in single query search speed, allows near instant search of big databases, scales to multiple GPUs and is fast beyond VRAM. It enables ColabFold MSA generation in seconds and sub-second Foldseek search against AFDB50. 1/n
📄 www.nature.com/articles/s41...
💿 mmseqs.com

GPU-accelerated homology search with MMseqs2 - Nature Methods

Graphics processing unit-accelerated MMseqs2 offers tremendous speedups for homology retrieval from metagenomic databases, query-centered multiple sequence alignment generation for structure predictio...

www.nature.com

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Seth Stadick @ducktapeprogrammer.bsky.social · Sep 12

Some very interesting preliminary benchmarks between Stringzilla and some Rust libs from Ash: x.com/ashvardanian...

Including some alignment comparisons.

Ash Vardanian on X: "Let there be https://t.co/KbIf9uMiVC 🧵 So many great libraries in Rust - the perfect soil for a thematic benchmark - across hashing, similarity scoring, search, and sketching Write-up coming, but there are already some indicative intermediate results https://t.co/B4rGLllnXM" / X

Let there be https://t.co/KbIf9uMiVC 🧵 So many great libraries in Rust - the perfect soil for a thematic benchmark - across hashing, similarity scoring, search, and sketching Write-up coming, but there are already some indicative intermediate results https://t.co/B4rGLllnXM

x.com

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Heng Li @lh3lh3.bsky.social · Sep 10

Now preprinted at arxiv.org/abs/2509.07357

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Jim Shaw @jimshaw.bsky.social · Sep 7

Preprint out for myloasm, our new nanopore / HiFi metagenome assembler!

Nanopore's getting accurate, but

1. Can this lead to better metagenome assemblies?
2. How, algorithmically, to leverage them?

with co-author Max Marin @mgmarin.bsky.social, supervised by Heng Li @lh3lh3.bsky.social

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bioRxiv Bioinfo @biorxiv-bioinfo.bsky.social · Sep 7

High-resolution metagenome assembly for modern long reads with myloasm https://www.biorxiv.org/content/10.1101/2025.09.05.674543v1

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Sergey Nurk @sergeynurk.bsky.social · Sep 8

Amazing work!

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Zamin Iqbal @zaminiqbal.bsky.social · Sep 7

For anyone who has used pling for comparing plasmids using rearrangement distances ("how many structural events apart are these plasmids"), here's how to tweak parameters, and integrate it with typing info, and the host phylogeny
www.biorxiv.org/content/10.1...
github.com/iqbal-lab-or...

Clustering of plasmid genomes for genomic epidemiology by using rearrangement distances, with pling

Integration of plasmids into genomic epidemiology is challenging, because there are no clearly defined evolving-units (equivalent to species), and because plasmids appear to evolve as much by structur...

www.biorxiv.org

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bioRxiv Bioinfo @biorxiv-bioinfo.bsky.social · Sep 7

High-resolution metagenome assembly for modern long reads with myloasm https://www.biorxiv.org/content/10.1101/2025.09.05.674543v1

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Sergey Nurk @sergeynurk.bsky.social · Sep 6

Congratulations!!!

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Rayan Chikhi @rayanchikhi.bsky.social · Sep 3

🌎👩‍🔬 For 15+ years biology has accumulated petabytes (million gigabytes) of🧬DNA sequencing data🧬 from the far reaches of our planet.🦠🍄🌵

Logan now democratizes efficient access to the world’s most comprehensive genetics dataset. Free and open.

doi.org/10.1101/2024...

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Giulio Ermanno Pibiri @jermp.bsky.social · Sep 1

We are glad to announce that the next workshop “Data Structures in Bioinformatics” (DSB 2026) will take place in Venice, Italy, on *February 18-19*, 2026. dsb-meeting.github.io/DSB2026/ Book the dates! #DSB26

DSB 2026 Venice - February 18-19

Workshop Data Structures in Bioinformatics

dsb-meeting.github.io

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Shawn Burgess @burgesslab.bsky.social · Aug 15

#zebrafish genome update, our T2T assembly of the inbred strain of AB (M-AB) generated by my buddy Nori Sakai has now been released at NCBI and will be a second reference genome for zebrafish (GRCz12ab):

JBQAYU000000000.1 Danio rerio :: NCBI

www.ncbi.nlm.nih.gov

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Yo Akiyama @yoakiyama.bsky.social · Aug 5

Excited to share work with
Zhidian Zhang, @milot.bsky.social, @martinsteinegger.bsky.social, and @sokrypton.org
biorxiv.org/content/10.1...
TLDR: We introduce MSA Pairformer, a 111M parameter protein language model that challenges the scaling paradigm in self-supervised protein language modeling🧵

Scaling down protein language modeling with MSA Pairformer

Recent efforts in protein language modeling have focused on scaling single-sequence models and their training data, requiring vast compute resources that limit accessibility. Although models that use ...

biorxiv.org

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Molecular Biology and Evolution @molbioevol.bsky.social · Jul 30

Pospelova et al. present a comparative analysis of full-length sequences of IG/TR loci across 46 mammalian species, demonstrating these as rapidly evolving genomic regions, with implications for immunogenomics.

🔗 doi.org/10.1093/molbev/msaf152

#evobio #molbio

Pospelova et al. present a comparative analysis of adaptive immune loci across diverse mammalian species, uncovering relationships between locus architecture, characteristics of immune genes, and population dynamics. The artwork illustrates how the structure of immunoglobulin heavy chain loci influences gene variability in three representative species from the study – the mountain lion, the ring-tailed lemur, and European hedgehog.

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Adam Phillippy @aphillippy.bsky.social · Aug 1

Complete genomes alert! @glennislogsdon.bsky.social, @christinebeck.bsky.social, and I were on @scifri.bsky.social today talking about "Complex genetic variation in nearly complete human genomes"
📄 www.nature.com/articles/s41...
📻 www.sciencefriday.com/segments/65-...

65 Genomes Expand Our Picture Of Human Genetics

Researchers closely examined the genomes of 65 individuals to paint a more complex, and more complete, picture of human genetic diversity.

www.sciencefriday.com

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Sean Gibbons 🦠💩 @gibbological.bsky.social · Jul 31

You can get an accurate estimate of total bacterial biomass from stool metagenomes by simply normalizing by host read count, without needing any additional measurements.

Excellent work by UW Master's student Gechlang Tang in @asm.org #mSystems Journal.

journals.asm.org/doi/10.1128/...
🧵

Metagenomic estimation of absolute bacterial biomass in the mammalian gut through host-derived read normalization | mSystems

In this study, we asked whether normalization by host reads alone was sufficient to estimate absolute bacterial biomass directly from stool metagenomic data, without the need for synthetic spike-ins, ...

journals.asm.org

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Heng Li @lh3lh3.bsky.social · Jul 31

Longdust, a new tool to identify highly repetitive STRs, VNTRs, satellite DNA and other low-complexity regions (LCRs). Similar to SDUST but for long regions.
github.com/lh3/longdust

GitHub - lh3/longdust: Identify long STRs, VNTRs, satellite DNA and other low-complexity regions in a genome

Identify long STRs, VNTRs, satellite DNA and other low-complexity regions in a genome - lh3/longdust

github.com

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