AlphaGenome: advancing regulatory variant effect prediction.
Gen AI in Biotech. Genome. AI in BioTech. Part-2.
Date: 7/5/2025
Fields: AI, BioTech, AlphaGenome-advancing regulatory variant effect prediction with a unified DNA sequence model, messenger RNA (mRNA), RNA- seq, CAGE-seq, PRO-cap), splicing (splice sites, splice site usage, splice junctions), DNA accessibility (DNase-seq, ATAC-seq), histone modification (ChIP-seq), transcription factor binding (TF ChIP-seq), or chromatin conformation (Hi-C/micro-C)
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Paper: AlphaGenome: advancing regulatory variant effect prediction with a unified DNA sequence model. Žiga Avsec, Natasha Latysheva, Jun Cheng, Guido Novati, Kyle R. Taylor, Tom Ward, Clare Bycroft, Lauren Nicolaisen, Eirini Arvaniti, Joshua Pan, Raina Thomas, Vincent Dutordoir, Matteo Perino, Soham De, Alexander Karollus, Adam Gayoso, Toby Sargeant, Anne Mottram, Lai Hong Wong, Pavol Drotár, Adam Kosiorek, Andrew Senior, Richard Tanburn, Taylor Applebaum, Souradeep Basu, Demis Hassabis, Pushmeet Kohli. doi: https://doi.org/10.1101/2025.06.25.661532