Vanja (Ivan Kulakovskiy) (@halfacrocodile) profile picture

Vanja (Ivan Kulakovskiy)

@halfacrocodile

bald but bearded bioinformatics buddy

Joined March 2022
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Photo by Vanja (Ivan Kulakovskiy) (@halfacrocodile)Photo by Vanja (Ivan Kulakovskiy) (@halfacrocodile)Photo by Vanja (Ivan Kulakovskiy) (@halfacrocodile)Photo by Vanja (Ivan Kulakovskiy) (@halfacrocodile)Photo by Vanja (Ivan Kulakovskiy) (@halfacrocodile)Photo by Vanja (Ivan Kulakovskiy) (@halfacrocodile)Photo by Vanja (Ivan Kulakovskiy) (@halfacrocodile)Photo by Vanja (Ivan Kulakovskiy) (@halfacrocodile)Photo by Vanja (Ivan Kulakovskiy) (@halfacrocodile)Photo by Vanja (Ivan Kulakovskiy) (@halfacrocodile)
EPIC website is back online after a forced vacation week. 2 months before the final deadline, it is not too late to enter the fray!
Dmitry Penzar (@dmitrypenzar) profile pictureDmitry Penzar@dmitrypenzarSep 22
🧬 EPIC is open: the Eukaryotic Promoter and transcription Initiation prediction Challenge. The goal: predict where, and how strongly, RNA Pol II starts transcribing, from nothing but DNA sequence. At single-nucleotide, strand-specific resolution. epic.autosome.org 🧵 1/7
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Nikita Gryzunov (@nikitagryzunov) profile picture
Nikita Gryzunov@nikitagryzunovOct 19
(1/12) The IBIS post-challenge paper is out in @CellReports (doi.org/10.1016/j.celrep.202…). We report the results of the open community benchmark of human TF binding specificity models, with a closer look at what advanced models learn that classic PWMs do not.
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Dmitry Penzar (@dmitrypenzar) profile picture
Dmitry Penzar@dmitrypenzarSep 22
🧬 EPIC is open: the Eukaryotic Promoter and transcription Initiation prediction Challenge. The goal: predict where, and how strongly, RNA Pol II starts transcribing, from nothing but DNA sequence. At single-nucleotide, strand-specific resolution. epic.autosome.org 🧵 1/7
Image from Dmitry Penzar (@dmitrypenzar)
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Waggoner Lab (@LabWaggoner) profile picture
Waggoner Lab@LabWaggonerAug 5
An expanded codebook of human transcription factor DNA-binding specificity @Nature @BartDeplancke @EPFL_en @halfacrocodile @ArttuJolma @VorontsovIE @ImYellan @UofT #Hughes 🇨🇦🇷🇺🇨🇭 nature.com/articles/s41586-0…
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1/10 Did you know that molecular phenotypes of human skeletal muscles are vastly different? Meet FANTOMUS, the skeletal muscles promoterome-proteome atlas: fantomus.autosome.org doi.org/10.64898/2026.04.08.… with @AndreyBuyan @Al__Forrest @nikitagryzunov @MakeevVsevolod @ogusev_lab
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9/10 Finally, allele-specific analysis revealed 6653 single-nucleotide variants with a significant allelic imbalance, which were enriched by GTEx eQTLs, ADASTRA ASBs, and associated with total thigh muscle volume.
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10/10 The FANTOMUS atlas is available at fantomus.autosome.org: an interactive browser of skeletal muscles’ gene expression, protein abundance, TRE expression, and motif activity. Read more: biorxiv.org/content/10.64898…
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Dmitry Penzar (@dmitrypenzar) profile picture
Dmitry Penzar@dmitrypenzar18 Nov 2025
(1/13)Excited to share the outcome of the IBIS Challenge! The IBIS challenge united dozens of teams across the world in tackling the problem of modeling transcription factor (TF) binding specificity using a diverse collection of experimental datasets for understudied human TFs.
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Ilya Vorontsov (@VorontsovIE) profile picture
Ilya Vorontsov@VorontsovIE17 Nov 2025
Our paper on LARGE-scale benchmarking of motif discovery tools is published! nature.com/articles/s42003-0… It was a long, 7 years long journey, which coordinated efforts of 50+ researchers, proud to be on of them. More results from Codebook about poorly studied TFs are coming soon.
Cross-platform motif discovery and benchmarking to explore binding specificities of poorly studied...

Cross-platform motif discovery and benchmarking to explore binding specificities of poorly studied...

Communications Biology - Cross-platform benchmarking of DNA binding specificity models highlights top-performing motif discovery methods and demonstrates the potential of advanced models to capture...

nature.com
Vanja (Ivan Kulakovskiy) (@halfacrocodile) profile pictureVanja (Ivan Kulakovskiy)@halfacrocodile14 Nov 2024
(1/13) Excited to present the results of the large-scale benchmarking of DNA motif discovery tools using the Codebook data compendium on poorly studied human transcription factors and the Codebook Motif Explorer dx.doi.org/10.1101/2024.11.1… | mex.autosome.org⬇️
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Katie Galloway (@GallowayLabMIT) profile picture
Katie Galloway
@GallowayLabMIT26 Jun 2025
So you want to change transgene expression: just change your promoter, right? Changing the promoter increases RNA and thus protein levels. What more could be happening? [1/n] Well, promoters don’t just set RNA levels; they uniquely transform how RNAs are transmitted into protein levels. 🧵
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Eugene F. Baulin (@febos41) profile picture
Eugene F. Baulin@febos4110 Jun 2025
📢Job Alert: Postdoctoral Researcher in the Laboratory of RNA Algorithms @IMol_Institute, up to three years, fully funded by @NCN_PL Details here: euraxess.ec.europa.eu/jobs/3… #postdoc #Academia #Position #Job #Research #RNA #Structure #Bioinformatics #Poland #Warsaw #IMolPAS #NCN
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Nacho Molina 🇪🇺 (@molina_lab) profile picture
Nacho Molina 🇪🇺@molina_lab19 May 2025
🚨 New method alert! We developed HiddenFoot, a physics-inspired approach to decode single-molecule footprinting data and infer TF, nucleosome, and RNA Pol II binding profiles on individual DNA molecules. One molecule at a time! biorxiv.org/content/10.1101/…
Image from Nacho Molina 🇪🇺 (@molina_lab)
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(1/15) Yet another sweet bioinformatics "software+database" couple from our team: Meet MIXALIME, a framework for assessing allelic imbalance, and UDACHA, a database of allele-specific chromatin accessibility, read more at nature.com/articles/s41467-0…
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(14/15) We hope you will find MIXALIME and UDACHA useful in your study of regulatory sequence variants.
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(15/15) MIXALIME is written in Python, getting the stable version is as easy as 'pip install mixalime', and the source code plus tutorial are freely available at github.com/autosome-ru/MixAL…
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