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Jasmine Barra

@jasminebarra.bsky.social

Jasmine Barra @jasminebarra.bsky.social · 04/11/2025

We are on the cover of Nucleic Acids Research! doi.org/10.1093/nar/... Thanks to the Karakach team! (www.karakachlab.org) @dalhousieu.bsky.social. Cover image is a watercolour by my mom, Iudi Simon. A self-taught painter and a true talent. Thanks @narjournal.bsky.social for showcasing her work!

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Jasmine Barra @jasminebarra.bsky.social · 23/09/2025

Find in @narjournal.bsky.social our latest kPPA-CART, a new effective framework for your multi-omics analysis. 👉https://academic.oup.com/nar/article/doi/10.1093/nar/gkaf844/8257763?utm_source=authortollfreelink&utm_campaign=nar&utm_medium=email&guestAccessKey=44031ac6-ca6c-47a7-bea5-f5a13e8e45e3

academic.oup.com

Augmented kurtosis-based projection pursuit: a novel, advanced machine learning approach for multi-omics data analysis and integration

Abstract. Due to the heterogeneity of multi-omics data, exacting their maximum information potential remains a challenge. Whereas some solutions have been

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Reposted by Jasmine Barra

Dr. Tobias Karakach @karakachlab.bsky.social · 21/09/2025

Proof? • Improved breast cancer subtyping vs PAM50 • Links to survival + tumor mutational burden • Free R package + web app for the community 👉 www.karakachlab.org/software/int...

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Reposted by Jasmine Barra

Dr. Tobias Karakach @karakachlab.bsky.social · 21/09/2025

The solution: kPPA-CART It digs into those low-signal regions, integrates transcriptomics, proteomics & methylation data, and finds real biological meaning others miss.

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Reposted by Jasmine Barra

Dr. Tobias Karakach @karakachlab.bsky.social · 21/09/2025

What’s the problem? 🤔 Most computational tools in bioinformatics only detect strong, obvious signals. Subtle, low-intensity features (the ones that really matter for biology) get lost in the noise.

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Reposted by Jasmine Barra

Dr. Tobias Karakach @karakachlab.bsky.social · 21/09/2025

Like Dj Khalid, another one from the KarakachLab! We just dropped kPPA-CART in @narjournal.bsky.social, a new machine learning method that finds hidden signals in messy multi-omics data. From kidney aging 🧬 to breast cancer 🎗️, it uncovers patterns others miss. doi.org/10.1093/nar/...

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