6 citations · 16 across the 7 of their papers we have counts for
4 papers · 1 filter
Entropy, Disagreement, and the Limits of Foundation Models in Genomics
Maxime Rochkoulets, Lovro Vrček, Mile Šikić
Foundation models in genomics have shown mixed success compared to their counterparts in natural language processing. Yet, the reasons for their limited effectiveness remain poorly…
Finding Hamiltonian cycles with graph neural networks
Filip Bosnić, Mile Šikić
We train a small message-passing graph neural network to predict Hamiltonian cycles on Erdős-Rényi random graphs in a critical regime. It outperforms existing hand-crafted heuristi…
A step towards neural genome assembly
Lovro Vrček, Petar Veličković, Mile Šikić
De novo genome assembly focuses on finding connections between a vast amount of short sequences in order to reconstruct the original genome. The central problem of genome assembly…
Read classification using semi-supervised deep learning
Tomislav Šebrek, Jan Tomljanović, Josip Krapac +1
In this paper, we propose a semi-supervised deep learning method for detecting the specific types of reads that impede the de novo genome assembly process. Instead of dealing direc…