Thomas Dyhre Nielsen — accepted AI-conference papers

2024

Revisiting K-mer Profile for Effective and Scalable Genome Representation Learning

Abdulkadir Celikkanat, Andres R Masegosa, Thomas Dyhre Nielsen

NeurIPS 2024spotlight

Obtaining effective representations of DNA sequences is crucial for genome analysis. Metagenomic binning, for instance, relies on genome representations to cluster complex mixtures of DNA fragments from biological samples with the aim of determining their microbial compositions. In this paper, we re…

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2023

Metagenomic Binning using Connectivity-constrained Variational Autoencoders

Andre Lamurias, Alessandro Tibo, Katja Hose, Mads Albertsen, Thomas Dyhre Nielsen

ICML 2023poster

Current state-of-the-art techniques for metagenomic binning only utilize local features for the individual DNA sequences (contigs), neglecting additional information such as the assembly graph, in which the contigs are connected according to overlapping reads, and gene markers identified in the cont…

Cited by 10 Source ↗PDF ↗Scholar ↗