Jorge Avila Cartes

PanSpace is a convolutional neural network-based tool for fast and scalable indexing of bacterial genome databases, reducing disk space and improving query speed.

This paper introduces deepSpecas, a deep learning method for differential analysis of alternative splicing events in RNA-seq samples, achieving higher precision with reduced sensitivity.

This paper introduces a method to construct pangenome graphs by solving an exact cover problem on blocks, showing how different objectives affect graph properties.

The paper develops CouGaR-g, a deep learning tool using FCGR and CNNs for accurate and fast clade assignment of SARS-CoV-2 sequences, achieving 96.29% accuracy on GISAID data.

The paper introduces RecGraph, a tool that extends sequence-to-graph alignment by incorporating recombinations, and evaluates its performance on bacterial pangenome graphs.