10 April 2024
Helmholtz Munich Campus
Europe/Berlin timezone

Whole Genome Transformers for Gene Interaction Effects in Microbiome Habitat Prediction

Not scheduled
1h
Auditorium, Building 23 (Helmholtz Munich Campus)

Auditorium, Building 23

Helmholtz Munich Campus

Ingolstädter Landstraße 1 · D-85764 Neuherberg
Poster Poster Break + Posters session

Description

Leveraging the vast genetic diversity within microbiomes offers unparalleled insights into complex phenotypes, yet the task of accurately predicting and understanding such traits from genomic data remains challenging. We propose a framework that leverages existing large models for gene vectorization to predict habitat specificity from entire microbial genome sequences. Based on our model, we develop attribution techniques to elucidate gene interaction effects that drive microbial adaptation to diverse environments. We train and validate our approach on a large dataset of high-quality microbiome genomes from different habitats. We not only demonstrate solid predictive performance but also pioneer leveraging sequence-level information of entire genomes to reveal the genetic foundations of complex phenotypes. Our attribution recovers known important interaction networks and proposes new candidates for experimental follow-up.

Primary authors

Prof. Niki Kilbertus (Helmholtz AI) Zhufeng Li (Helmholtz AI)

Co-authors

Mr Nicholas Youngblut (Arc Institute) Mr Sandeep Suresh Cranganore (Forschungszentrum jülich)

Presentation materials

There are no materials yet.