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Posts by Kristina Gagalova, Bioinformatics scientist

Ourt super star, Pavel, is giving the first PhD Milestone. Looking forward to hear more about AI applied to protein-protein interactions

1 month ago 2 0 0 0
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As we lead up to #IWD2026, we’re celebrating Kristina Gagalova, Bioinformatics Scientist and part of AGGI, whose work bridges cutting‑edge genomics with real‑world agricultural impact.
@curtinuniversity.bsky.social, #GRDC

1 month ago 3 2 0 0
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Technical Lead Biostatistics Job in Nedlands, Perth WA - SEEK Life-changing science is our focus; we start there, and everything else follows

We (PYC Therapeutics) are hiring two biostatisticians, one senior, one junior

www.seek.com.au/job/90561321...
and
www.seek.com.au/job/90560959...

We need people who can give us confidence in rare disease diagnostics with small n!

#biostatistics

1 month ago 4 2 1 0

kache-hash: A dynamic, concurrent, and cache-efficient hash table for streaming k-mer operations www.biorxiv.org/content/10.64898/2026.02...

2 months ago 10 7 0 0
Streamlit

Webserver
she-app.serve.scilifelab.se

2 months ago 0 0 0 0

Preprint
www.biorxiv.org/content/10.6...

2 months ago 0 0 0 0

SHE reconstructs eukaryotic evolution using structural comparisons across 1542 proteomes. It reveals a rigid Strict Core supporting a flexible translational Operational Engine, detects lineagespecific accelerations, and uses structural topology to see proteome quality and guide model organism choice

2 months ago 0 0 2 0
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The Dayhoff Atlas: scaling sequence diversity improves protein design - Microsoft Research A collection of both protein sequence data and generative models, designed to serve as a modern resource for protein biology in the age of AI.

More details here
www.microsoft.com/en-us/resear...

2 months ago 1 0 0 0

Dayhoff Atlas release is a big step for protein language models and generative protein design. By opening up massive protein datasets + pretrained models, it lowers the barrier for researchers to predict mutation effects, and generate functional sequences #ProteinAI #ProteinDesign #MicrosoftResearch

2 months ago 1 1 1 0
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Multiple protein structure alignment at scale with FoldMason Protein structure is conserved beyond sequence, making multiple structural alignment (MSTA) essential for analyzing distantly related proteins. Computational prediction methods have vastly extended ou...

FoldMason is out now in @science.org. It generates accurate multiple structure alignments for thousands of protein structures in seconds. Great work by Cameron L. M. Gilchrist and @milot.bsky.social.
πŸ“„ www.science.org/doi/10.1126/...
🌐 search.foldseek.com/foldmason
πŸ’Ύ github.com/steineggerla...

2 months ago 301 147 4 3
Figure 1. Workflow of fDOG-Assembly. (A) fDA starts its ortholog search from a pre- computed core ortholog group together with a multiple sequence alignment (MSA) of the corresponding amino acid sequences, and a profile Hidden Markov Model (pHMM) trained with the MSA. A consensus sequence is computed from the pHMM, and the MSA is used to produce a block profile. (B) A tblastn search with the consensus sequence as query identifies candidate regions in the target genome assembly that may harbour an ortholog. (C) Each candidate region from (B) serves as input for a gene prediction. fDOG-Assembly provides two alternative ways for gene prediction, Augustus in combination with the pre-computed block profile or MetaEuk in combination with a reference database. (D) To verify the ortholog candidates resulting from (C), the amino acid sequences of the predicted genes (ortholog candidates) are used as queries in a reverse blastp search in the protein set of a user-specified reference species. If two or more candidate orthologs are verified, only those are accepted as co-orthologs whose pair-wise distance is smaller than their respective distances to the reference protein. Otherwise, the candidate with the smaller distance is chosen. See main text for further information on the candidate verification. An assessment of the feature architecture similarities of the identified orthologs and the seed gene concludes the ortholog search.

Figure 1. Workflow of fDOG-Assembly. (A) fDA starts its ortholog search from a pre- computed core ortholog group together with a multiple sequence alignment (MSA) of the corresponding amino acid sequences, and a profile Hidden Markov Model (pHMM) trained with the MSA. A consensus sequence is computed from the pHMM, and the MSA is used to produce a block profile. (B) A tblastn search with the consensus sequence as query identifies candidate regions in the target genome assembly that may harbour an ortholog. (C) Each candidate region from (B) serves as input for a gene prediction. fDOG-Assembly provides two alternative ways for gene prediction, Augustus in combination with the pre-computed block profile or MetaEuk in combination with a reference database. (D) To verify the ortholog candidates resulting from (C), the amino acid sequences of the predicted genes (ortholog candidates) are used as queries in a reverse blastp search in the protein set of a user-specified reference species. If two or more candidate orthologs are verified, only those are accepted as co-orthologs whose pair-wise distance is smaller than their respective distances to the reference protein. Otherwise, the candidate with the smaller distance is chosen. See main text for further information on the candidate verification. An assessment of the feature architecture similarities of the identified orthologs and the seed gene concludes the ortholog search.

Targeted ortholog search in unannotated genome assemblies with fDOG-Assembly
doi.org/10.1101/2025...

3 months ago 2 1 0 0
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Fifty years ago today: the Fall of Saigon, April 30, 1975. I remember seeing these images on TV as if it was yesterday.

#VietnamWar
#Saigon

11 months ago 2 1 1 0

Landing dock, such interesting piece of history

3 months ago 0 0 0 0
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πŸ“š On my 2026 reading bucket list.
The "Quiet American" by Graham Greene, set in 1950s Saigon, at the end of French colonial rule and the start of U.S. involvement in Vietnam. A sharp, unsettling look at good intentions and their consequences.
#ReadingBucketList
#Saigon #HoChiMinhCity
#BookBucketList

3 months ago 2 0 0 0
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Exploring and Analyzing LC-MS Data This resource hosts tutorials and end-to-end workflows describing how to analyze LC-MS/MS data, from raw files to annotation, using Bioconductor packages.

rformassspectrometry.github.io/Metabonaut/

3 months ago 3 2 0 0
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1/4 Ever wanted to predict bacterial protein-protein interactions (PPI) on a large scale?
We wanted to, but realized there’s no such algorithm that is both rapid and optimized for bacterial protein analysis.
This led our ⭐️Chen Agassy⭐️ to develop B-PPI: doi.org/10.64898/202...

3 months ago 5 3 1 0
https://doi.org/10.1186/s12915-025-02455-w

https://doi.org/10.1186/s12915-025-02455-w

https://doi.org/10.1186/s12915-025-02455-w

https://doi.org/10.1186/s12915-025-02455-w

ntSynt: multi-genome synteny detection using minimizer graph mappings
doi.org/10.1186/s129...

3 months ago 33 5 0 0

Benchmarking

3 months ago 2 0 0 0
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#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 ➑️ tinyurl.com/Genome-Res-2...

5 months ago 10 5 0 1
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2.1 Reading Trees Chapter contents: Systematics β€” 1. Taxonomy β€” 2. Phylogenetics β€”β€” 2.1 Reading trees ← β€”β€” 2.2 Building trees β€”β€” 2.3 Character mapping β€”β€” 2.4 Phylogenetic trees and classificationParts of a tree A phylo...

If you're a #teacher interested in a great #openaccess write up on reading #phylogenetic trees, check out www.digitalatlasofancientlife.org/learn/system... created by @jonhendricks.bsky.social and Elizabeth Hermsen.

5 months ago 41 18 0 0
An oil portrait painting of Mary Somerville, the renowned 19th-century Scottish mathematician, astronomer, and science writer, by Thomas Phillips (1834). She is depicted as a poised woman in her fifties, facing slightly to the left with a calm, intelligent expression. Her dark hair is elegantly styled, parted in the center and drawn up into intricate braids with soft ringlets framing each side of her face. She wears a formal dark blue or black off-the-shoulder gown with puffed sleeves, draped in a luxurious brown fur stole over her shoulders. A wide, elaborate white lace ruff collar frames her neck, and at the center of her chest is a prominent emerald-green brooch set in gold, fastened to the gathered fabric. The background is a dramatic, dark gradient with subtle warm highlights, employing chiaroscuro lighting to emphasize her serene face and the textures of lace, fur, and fabric, evoking a sense of dignified intellect and refinement typical of Regency-era portraiture.

An oil portrait painting of Mary Somerville, the renowned 19th-century Scottish mathematician, astronomer, and science writer, by Thomas Phillips (1834). She is depicted as a poised woman in her fifties, facing slightly to the left with a calm, intelligent expression. Her dark hair is elegantly styled, parted in the center and drawn up into intricate braids with soft ringlets framing each side of her face. She wears a formal dark blue or black off-the-shoulder gown with puffed sleeves, draped in a luxurious brown fur stole over her shoulders. A wide, elaborate white lace ruff collar frames her neck, and at the center of her chest is a prominent emerald-green brooch set in gold, fastened to the gathered fabric. The background is a dramatic, dark gradient with subtle warm highlights, employing chiaroscuro lighting to emphasize her serene face and the textures of lace, fur, and fabric, evoking a sense of dignified intellect and refinement typical of Regency-era portraiture.

Scottish mathematician, astronomer & polymath Mary Somerville was born #OTD in 1780. #WomenInSTEM

William Whewell coined the term "scientist" in a review of Somerville's book, π˜–π˜― 𝘡𝘩𝘦 𝘊𝘰𝘯𝘯𝘦𝘹π˜ͺ𝘰𝘯 𝘰𝘧 𝘡𝘩𝘦 π˜—π˜©π˜Ίπ˜΄π˜ͺ𝘀𝘒𝘭 𝘚𝘀π˜ͺ𝘦𝘯𝘀𝘦𝘴. Used as gender-neutral term as the common term at the time was "man of science."

3 months ago 211 91 1 4

Bookmarking

3 months ago 0 0 0 0

Bookmarking πŸ”–

4 months ago 2 0 0 0
The GraSuite Logo a suite and a tie showing a graph, with a double strand DNA symbolized on the right

The GraSuite Logo a suite and a tie showing a graph, with a double strand DNA symbolized on the right

In conclusion, GraTools is a powerful too for a one-tool manipulation of GFA pangenome variation graphs!

It is a member of the GraSuite, feel free to discover !

forge.ird.fr/diade/GraSuite

4 months ago 1 1 1 0

Where are you heading to? Or are you going to release the secret in 3 weeks? πŸ˜‰

4 months ago 1 0 1 0
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This year, we celebrate Margaret Dayhoff’s 100th birthday. She built the first protein database when computers filled entire rooms, introduced the amino acid code, and worked on substitution matrices we still rely on today.
#Bioinformatics #WomenInSTEM #HistoryOfScience #SciencePioneer

4 months ago 26 12 0 0
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Ready to take your involvement with the Nextflow community to the next level?⬆️ Apply to become a Nextflow Ambassador by Dec 20, 2025!🧡

πŸ“š Learn more: hubs.la/Q03V9PSs0
πŸ”— Apply here: hubs.la/Q03V9PQQ0

#Bioinformatics #DataScience

5 months ago 6 4 1 0
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Jarritos gummies? Yeah

5 months ago 2 0 0 0
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I recently damaged an entire repo trying to remove a large file I added 2 commits ago... "I don't know what I did" moment

6 months ago 1 0 0 0
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RIP to Jane Goodall, who opened the world's eyes to our closest relatives. (Photo by NatGeo's Hugo Van Lawick)

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