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Chakravarthi Kanduri

@chakri.bsky.social

Researcher at the University of Oslo | PhD in #Bioinformatics from University of Helsinki | academic #datascience, #python, #rstats, #ML

Posts Replies Media

Reposted by Chakravarthi Kanduri

Gur Yaari @guryaari.bsky.social · 14/11/2025

Ready to make your mark? Accept the challenge 👇 🔗: kaggle.com/competitions... #AIRR #Competition #DeepLearning #ComputationalBiology @victorgreiff.bsky.social @chakri.bsky.social

kaggle.com

AIRR-ML-25: Adaptive Immune Profiling Challenge

Predict labels (e.g. disease, healthy) from sets of immune receptor sequences, and identify the sequences that explain the labels.

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Reposted by Chakravarthi Kanduri

Greifflab @victorgreiff.bsky.social · 22/10/2025

📢 We are announcing the Adaptive Immune Profiling Challenge 2025! Can you predict immune state labels from adaptive immune receptor repertoires? 💰 $10,000 prize pool! 🗓️ Launches Nov 5 on @kaggle.com More Info: uio-bmi.github.io/adaptive_imm...

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Chakravarthi Kanduri @chakri.bsky.social · 18/08/2025

1/12 🧵 Quick thread: a heads-up for anyone working with high-dimensional omics data and multiple testing — FDR correction can sometimes lie to you. A thread based on our recent publication in @GenomeBiology : doi.org/10.1186/s130...

doi.org

Beware of counter-intuitive levels of false discoveries in datasets with strong intra-correlations - Genome Biology

The false discovery rate (FDR) controlling method by Benjamini and Hochberg (BH) is a popular choice in the omics fields. Here, we demonstrate that in datasets with a large degree of dependencies betw...

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Reposted by Chakravarthi Kanduri

Puneet Rawat, PhD @puneet021192.bsky.social · 14/12/2024

Happy to share our new collaborative work! 🚨 We analyzed 2250 TCR repertoires to uncover how HLA risk alleles shape immune autoreactivity in T1D. T1D-specific HLA-motifs were also validated in pancreatic lymph nodes (pLN) & spleen. 🧬🧵 #T1D #Immunology #TCR 1/9

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Reposted by Chakravarthi Kanduri

Greifflab @victorgreiff.bsky.social · 24/10/2023

Machine learning on immune receptors/repertoires is an exponentially expanding field, but labeled data to benchmark ML methods are missing. We address this need with our new simulation framework LIgO. www.biorxiv.org/content/10.1... Led by @mchernigovskaya.bsky.social and Milena Pavlović.

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