We made three pangenome graphs 🧬 public, one for the Japanese, one for the Saudi population, and a merged graph (JaSaPaGe). Useful for 🖥️ bioinformatics on either population, or to evaluate how pangenome graphs behave when two different populations are included. jasapage.bio2vec.net/view for PanGene

ProtBoost: protein function prediction with Py-Boost and Graph Neural Networks -- CAFA5 top2 solution The second-place solution in CAFA5 has now been published. Paper: arxiv.org/abs/2412.045... GitHub Repo: github.com/btbpanda/CAF... Kaggle Writeup: www.kaggle.com/competitions...

Proud to share our new paper! A complete genome from Saudi Arabia (KSA001), freely available to all. Complex work - not just sequencing & assembly challenges, but also navigating IRB approval to ensure ethical data sharing & open science principles. nature.com/articles/s41...

I am excited to share that our paper on creating a very large structure causal model for diseases has been published. We generate an SCM containing most common diseases, and validate with #UKBiobank data, for better polygenic scores, and finding pleitropic variants academic.oup.com/bioinformati...