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sinamajidian.bsky.social
Sina Majidian
@sinamajidian.bsky.social
1.3K followers 1.6K following 140 posts
On the academic job market | How are species compared to one another across different genomic regions? Postdoc at Langmead Lab, Johns Hopkins | Comparative #genomics at scale | Formerly at UNIL/SIB/WUR | sinamajidian.github.io
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sinamajidian.bsky.social
Sina Majidian @sinamajidian.bsky.social · Jan 3
FastOMA is out now in Nature Methods 🎉: nature.com/articles/s41592-024-02552-8 A new orthology inference algorithm that scales linearly and is highly accurate. FastOMA can process all >2000 eukaryotic UniProt ref proteomes <24 hours 🚀. Try it out github.com/DessimozLab/fastoma @dessimoz.bsky.social
FastOMA retains OMA’s high precision accuracy and even improves upon it in terms of recall, positioning it on the Pareto frontier of orthology inference methods. FastOMA is not only fast but also accurate. a, QfO benchmar, agreement with SwissTree reference phylogeny covering manually curated gene trees. The error bars indicate 95% confidence intervals comparing FastOMA with EnsemblCompara, Domainoid, OrthoMCL, Ortholnspector, sonicparanoid, PANTHER, OrthoFinder, Hieranoid26 and the OMA family including OMA pairs, OMA groups and OMA GETHOGs (graph-based efficient technique for HOGs). c) A computation time comparison of FastOMA and state-of-the-art alternatives. https://www.nature.com/articles/s41592-024-02552-8
Reposted by Sina Majidian
margaretbrisbin.bsky.social
Hey #microbialsky - anyone looking for a good PhD student this cycle? Ugrad from my lab is looking but no luck with the PIs she has contacted (no funding, no response). She worked in my lab for 1.5 years, now is a research tech at the FWC research institute. Excellent at the bench & super smart!
November 26, 2025 at 1:36 AM
Reposted by Sina Majidian
josephguhlin.bsky.social
Help. Can anyone in my network (or outside) endorse me for arXiv q-bio? #breeding #breeding
November 25, 2025 at 6:47 PM
Reposted by Sina Majidian
jonnyfrazer.bsky.social
popEVE is out in Nature Genetics! 🎉
We built a proteome-wide model that combines cross-species and human population variation to rank missense variants by disease severity and help diagnose rare genetic disorders.
rdcu.be/eRu7K
Proteome-wide model for human disease genetics
Nature Genetics - popEVE is a proteome-wide deep generative model to identify and predict pathogenicity of missense mutations causing genetic disorders.
rdcu.be
November 24, 2025 at 1:35 PM
Reposted by Sina Majidian
camillemrcht.bsky.social
Colored graphs (+abundances), low density minimizers and quick sequence parse 🚀
November 24, 2025 at 9:14 AM
Reposted by Sina Majidian
hillermich.bsky.social
Happy to present TOGA2, developed by Yury Malovichko @ymalovichko.bsky.social, the faster, memory-efficient & more accurate TOGA1 successor (github.com/hillerlab/TO...). And annotations, orthologs & gene loss/dup data generated with 4 references for 883 placental mammal and with 5 refs for 676 ...
November 23, 2025 at 9:49 PM
sinamajidian.bsky.social
Our trilogy of orthology publications is online!
Review on Hierarchical Orthologous Groups doi.org/10.1007/s00239-025-10277-1

OrthoXML-Tools doi.org/10.1007/s00239-025-10271-7

A great community effort on Quest for Orthologs in the era of Data Deluge and AI doi.org/10.1007/s00239-025-10272-6
https://link.springer.com/article/10.1007/s00239-025-10277-1 Conceptual overview of hierarchical orthologous groups. An example of one HOG, or gene family. A Species tree with four taxa: plant (green), fish (blue), human (orange), and mouse (yellow), each with one or more genes. B The implied gene tree, dubbed “HOG tree,” and inferred nested HOG composition. Duplication nodes (red) can be deduced based on the species tree topology and clusters of homologous genes at each level. Ancestral genes from which the HOGs descended are shown in gray. C HOGs returned at different taxonomic levels. Consider a gene family that was present in the last eukaryotic common ancestor (LECA). At this level, a single HOG encompasses all genes descending from that ancestral gene. At the Vertebrata level, this gene underwent duplication, leading to two distinct copies, i.e., HOGs. At the Mammalia level, a second duplication further subdivides one of these HOGs, showing how deeper HOGs split into nested subHOGs at more recent levels. The HOG composition implies that a loss event occurred after the mammalian speciation https://link.springer.com/article/10.1007/s00239-025-10272-6 Summary of the QfO8 meeting. a Hot topics and future directions in method development and applications within the QfO community, namely artificial intelligence, protein domains, protein structure, RNA and splicing isoforms. b Definition of orthology and paralogy, including various paralogous subtypes (e.g. in-paralogs and out-paralogs). c Duplications and functional divergence. d Applications of orthology https://link.springer.com/article/10.1007/s00239-025-10271-7 Overview of the OrthoXML File Format (simplified). A schematic representation of an OrthoXML file, a standardized XML-based format for representing orthology data. OrthoXML follows a hierarchical structure where elements are enclosed within opening < tag > and closing </tag > tags. < orthoXML > is the root element enclosing other elements. The < species > element contains information about genes. An OrthoXML file can include a < taxonomy > element, which specifies the species tree used to generate the file. Additionally, the < groups > element encapsulates the orthology and paralogy relationships among genes
November 21, 2025 at 4:26 PM
Reposted by Sina Majidian
physaliacourses.bsky.social
Most courses in December are now fully booked or have only a few seats remaining.

If you or your colleagues were planning to register, please secure your spot right away!

www.physalia-courses.org/courses-work...

#Phylogenomics #StructuralVariants #GAMs #Rstats #Genviz #MultiOmics #Bioinformatics
November 19, 2025 at 3:44 PM
sinamajidian.bsky.social
The giant wakes up: Illumina goes spatial
www.batcheffect.com/p/the-giant-...
The giant wakes up: Illumina goes spatial
Predictions on the upcoming Illumina spatial transcriptomics technology
www.batcheffect.com
November 19, 2025 at 1:18 PM
Reposted by Sina Majidian
danielkhashabi.bsky.social
For years since the GPT-2 paper, emergent in-context learning (ICL) from 'next-token' training has been treated as something deeply tied to 𝐡𝐮𝐦𝐚𝐧 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞. But … is it?
November 18, 2025 at 5:27 PM
Reposted by Sina Majidian
irenejulca.bsky.social
Interested in the newest developments in orthology? Check out the last Quest for Orthologs (QfO9) meeting report:
link.springer.com/article/10.1...
#orthology #function #domains #AI #paralogy
Thanks to @sinamajidian.bsky.social and all co-authors for their valuable contribution.
November 18, 2025 at 11:52 AM
Reposted by Sina Majidian
zaminiqbal.bsky.social
Honoured and quite blown-over to receive this award. I have been, and continue to be, very lucky - first with great mentors, and then really prodigious students, postdocs and collaborators. Working with them has been a joy.
gensocuk.bsky.social Genetics Society UK @gensocuk.bsky.social · 11d
Congratulations to @zaminiqbal.bsky.social from @milnerevolution.bsky.social on being awarded the 2026 Mary Lyon Medal!
November 14, 2025 at 12:55 PM
Reposted by Sina Majidian
pkoo562.bsky.social
Exciting symposium on AI and Biology at EMBO | EMBL in Heidelberg on 10-13 March 2026!

Excellent lineup of invited speakers across various scales of biology!

Deadline for abstract submission is coming up — Dec 2.

🔗 www.embl.org/about/info/c...

#EESAIBio @EMBLEvents
November 7, 2025 at 12:16 AM
Reposted by Sina Majidian
sedlazeck.bsky.social
From coffee-fueled coding marathons ☕ to new genomics tools: Our 2024 #Hackathon paper is out in @f1000publishing.bsky.social !
Huge thanks to everyone world wide who joined the @bcmhgsc.bsky.social madness 🎉
🔗 f1000research.com/articles/14-...
@gregor-research.bsky.social @smahtnetwrk.bsky.social
November 10, 2025 at 2:25 PM
Reposted by Sina Majidian
Thank you folks for your feedback on our survey about Hash functions in genomic sequence analysis. We've updated the paper and you can see the new version here: tinyurl.com/4kk9ccmt.
September 25, 2025 at 1:21 PM
Reposted by Sina Majidian
gamfeldt.bsky.social
Opportunity!
Anybody knows of young marine ecologists (within 7 years from earned PhD) that would like to come to Gothenburg, Sweden, for a nationally funded Assistant Professorship? It is highly competitive but well funded. (1) of (3)
November 10, 2025 at 9:32 AM
sinamajidian.bsky.social
Specificity, length and luck drive gene rankings in association studies
nature.com/articles/s41586-025-09703-7
a,b, Schematics of GWAS (a) and LoF burden tests (b). c, Each cell is a genome-wide significant gene according to LoF burden tests, ordered by significance (most significant (top) to least significant (bottom)). Genes are coloured by the rank of the locus that contains the gene according to GWAS or are coloured black if they are not contained in any genome-wide significant locus. Across 151 traits with at least one burden hit and one GWAS hit, 74.6% (1,382 out of 1,852) of genome-wide significant burden test hits fall within a GWAS locus. Trait abbreviations are defined in Supplementary Table 1. d, Minimum LoF burden test P values for any gene overlapping a genome-wide significant GWAS locus plotted against the minimum GWAS P value within that locus (n = 382 loci). e, The genomic region surrounding NPR2. GWAS P values of approximately independent genome-wide significant GWAS hits (top), and the location of genes coloured by LoF burden test P values (bottom) are shown. f, Similar to panel e but for the genomic region surrounding HHIP. a, A cartoon of two genes that affect a trait under study. The widths of the arrows represent the relative effect sizes. Gene 1 is more trait specific, but gene 2 is more trait important. b, Formal definitions of trait importance and trait specificity for genes in the context of LoF burden tests.
November 9, 2025 at 12:52 PM
Reposted by Sina Majidian
mnguyen667.bsky.social
Finally on BlueSky, and happy to have had the opportunity to give a talk at Genome Informatics!
sinamajidian.bsky.social Sina Majidian @sinamajidian.bsky.social · 18d
Matthew Nguyen delivered a great talk on "Refining Kraken2 long-read taxonomic classifications using convolutional neural networks"
November 8, 2025 at 5:27 PM
Reposted by Sina Majidian
vikramshivakumar.bsky.social
Really excited to see our new work in scaling Mumemto to any size pangenome published in Genome Research this morning. And right on cue with the great opportunity to present this work at #GI2025 this week.
genomeresearch.bsky.social Genome Research @genomeresearch.bsky.social · 18d
#GI2025 Vikram Shivakumar from Ben Langmead's lab (@benlangmead.bsky.social) presents "MumemtoM - partitioned Multi-MUM finding for scalable pangenomics ". Now published in Genome Research @genomeresearch.bsky.social. Read full text here ➡️ tinyurl.com/Genome-Res-2...
November 7, 2025 at 9:29 PM
sinamajidian.bsky.social
Third day of Genome Informatics #GI2025 began with an exciting session on “AI, ML and Integrative Genomics” chaired by Irene Kaplow & Thomas Pierrot.
The first talk, by Irene Kaplow, focused on Challenges in Predicting Enhancer Activity Differences Between Species
doi.org/10.1186/s12864-022-08450-7
OCR Ortholog Open Chromatin Status Prediction Framework Overview. a We trained a convolutional neural network (CNN) for predicting brain open chromatin using sequences underlying brain open chromatin region (OCR) orthologs in a small number of species and used the CNN to predict brain OCR ortholog open chromatin status across the species in the Zoonomia Consortium. Specifically, we used the sequences underlying the orthologs for which we have brain open chromatin data to train a CNN for predicting open chromatin. Then, we used the CNN to predict the probability of brain open chromatin for all brain OCR orthologs; predictions are illustrated on the right. Animals for which we do not have open chromatin data are in dark gray instead of black to indicate that their brain open chromatin is imputed. While we cannot evaluate the accuracy of most of our predictions, obtaining open chromatin data from most tissues in most species is infeasible, so predictions might be the best OCR annotations that we can obtain. b To demonstrate that our models can accurately predict whether sequence differences between species are associated with open chromatin differences, in addition to the evaluations described in previous work [57], we evaluated our performance on species-specific open chromatin for a species not used in model training and clade-specific open and closed chromatin for clades not used in model training. Since such regions often comprise a minority of OCR orthologs, models could obtain good overall performance while obtaining poor performance on such regions. We also evaluated our performance on tissue-specific open and closed chromatin for a tissue not used in model training, where we expect models to predict 0 if model learns sequence signatures related to the tissue used in training. c Full mouse test set and lineage-specific OCR accuracy evaluations for mouse sequence-only brain model, illustrating that, even for the best of these models,
November 7, 2025 at 2:28 PM
Reposted by Sina Majidian
genomeresearch.bsky.social
#GI2025 Mile Sikic @msikic.bsky.social presents "Geometric deep learning framework for de novo genome assembly" Now published in GenomeResearch @genomeresearch.bsky.social Full text here ➡️ tinyurl.com/Genome-Res-2...
November 6, 2025 at 10:33 PM
sinamajidian.bsky.social
Second day of Genome Informatics #GI2025 began with the session “Genome Assembly and Sequence Algorithms" Yun William Yu presented “Average-case Analysis of Seed-Chain-Extend under Random Mutations"
genome.cshlp.org/content/33/7/1175
providing theoretical guarantees for the popular seed-chain-extend
Abstract: Seed-chain-extend with k-mer seeds is a powerful heuristic technique for sequence alignment used by modern sequence aligners. Although effective in practice for both runtime and accuracy, theoretical guarantees on the resulting alignment do not exist for seed-chain-extend. In this work, we give the first rigorous bounds for the efficacy of seed-chain-extend with k-mers in expectation. Assume we are given a random nucleotide sequence of length ∼n that is indexed (or seeded) and a mutated substring of length ∼m ≤ n with mutation rate θ < 0.206. We prove that we can find a k = Θ(log n) for the k-mer size such that the expected runtime of seed-chain-extend under optimal linear-gap cost chaining and quadratic time gap extension is O(mn^f(θ) log n), where f(θ) < 2.43 · θ holds as a loose bound. The alignment also turns out to be good; we prove that more than 1-o(sqrt(1/m)) fraction of the homologous bases is recoverable under an optimal chain. We also show that our bounds work when k-mers are sketched, that is, only a subset of all k-mers is selected, and that sketching reduces chaining time without increasing alignment time or decreasing accuracy too much, justifying the effectiveness of sketching as a practical speedup in sequence alignment. We verify our results in simulation and on real noisy long-read data and show that our theoretical runtimes can predict real runtimes accurately. We conjecture that our bounds can be improved further, and in particular, f(θ) can be further reduced.
November 6, 2025 at 2:19 PM
sinamajidian.bsky.social
Ben Langmead @benlangmead.bsky.social delivers the official opening for this year's Genome Informatics Conference #GI2025 at Cold Spring Harbor Laboratory.
List of talks and posters: meetings.cshl.edu/abstracts.as...
November 6, 2025 at 12:38 AM
sinamajidian.bsky.social
Excited to be at the Genome Informatics conference #GI2025 in Cold Spring Harbor Laboratory this week! I’ll be sharing my current work on using machine learning to improve the reliability of Metagenomics classification for analzing gut microbiota and soil samples. Let's connect!
November 4, 2025 at 8:51 PM
Reposted by Sina Majidian
pengellab.bsky.social
🐝🦠 New paper: rdcu.be/eOf7A
Phages may drive microbial diversity, yet we often don’t even know how phages & bacteria correlate in nature. Our new study tackles this in the honeybee gut, thanks to the great work of PhD student @malickndiaye.bsky.social at @dmf-unil.bsky.social @fbm-unil.bsky.social
Phage diversity mirrors bacterial strain diversity in the honey bee gut microbiota - Nature Communications
Authors analyse paired viral and bacterial shotgun metagenomics data from individual honeybee guts, revealing modular, nested phage–bacteria networks, with viral diversity mirroring bacterial strain c...
www.nature.com
November 4, 2025 at 8:36 PM