Matias Gerard

According to our database, Matias Gerard authored at least 17 papers between 2009 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

MOELIGA: a multi-objective evolutionary approach for feature selection with local improvement.

Leandro Daniel Vignolo, Matias Gerard

CoRR, March, 2026

2025

Comprehensive benchmarking of large language models for RNA secondary structure prediction.

Luciano I Zablocki, Leandro A. Bugnon, Matias Gerard, Leandro E. Di Persia, Georgina Stegmayer, Diego H. Milone

Briefings Bioinform., March, 2025

A Hybrid Supervised and Self-Supervised Graph Neural Network for Edge-Centric Applications.

Eugenio Borzone, Leandro E. Di Persia, Matias Gerard

IEEE Trans. Signal Inf. Process. over Networks, 2025

2024

sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure.

Leandro A. Bugnon, Leandro E. Di Persia, Matias Gerard, Jonathan Raad, Santiago Prochetto, Emilio Fenoy, Uciel Chorostecki, Federico Ariel, Georgina Stegmayer, Diego H. Milone

Briefings Bioinform., July, 2024

2022

Secondary structure prediction of long noncoding RNA: review and experimental comparison of existing approaches.

Leandro A. Bugnon, Alejandro A. Edera, Santiago Prochetto, Matias Gerard, Jonathan Raad, Emilio Fenoy, Mariano Rubiolo, Uciel Chorostecki, Toni Gabaldón, Federico Ariel, Leandro E. Di Persia, Diego H. Milone, Georgina Stegmayer

Briefings Bioinform., 2022

Neural Model-Based Similarity Prediction for Compounds with Unknown Structures.

Eugenio Borzone, Leandro Ezequiel Di Persia, Matias Gerard

Proceedings of the Applied Informatics: 5th International Conference, 2022

2020

PhDSeeker: Pheromone-Directed Seeker for metabolic pathways.

Matias Fernando Gerard, Raúl N. Comelli

Biosyst., 2020

DL4papers: a deep learning approach for the automatic interpretation of scientific articles.

Leandro A. Bugnon, Cristian A. Yones, Jonathan Raad, Matias Gerard, Mariano Rubiolo, Gabriela Alejandra Merino, Milton Pividori, Leandro E. Di Persia, Diego H. Milone, Georgina Stegmayer

Bioinform., 2020

2019

Predicting novel microRNA: a comprehensive comparison of machine learning approaches.

Georgina Stegmayer, Leandro E. Di Persia, Mariano Rubiolo, Matias Gerard, Milton Pividori, Cristian A. Yones, Leandro A. Bugnon, Tadeo Rodriguez, Jonathan Raad, Diego H. Milone

Briefings Bioinform., 2019

2017

Evolutionary local improvement on genetic algorithms for feature selection.

Leandro Daniel Vignolo, Matias Fernando Gerard

Proceedings of the 2017 XLIII Latin American Computer Conference, 2017

2016

Evolutionary algorithm for metabolic pathways synthesis.

Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone

Biosyst., 2016

2015

EvoMS: An evolutionary tool to find de novo metabolic pathways.

Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone

Biosyst., 2015

2014

Desarrollo de algoritmos evolutivos para el descubrimiento de relaciones en datos metabólicos

Matias Gerard

PhD thesis, 2014

2013

An evolutionary approach for searching metabolic pathways.

Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone

Comput. Biol. Medicine, 2013

2012

Data Mining Over Biological Datasets: An Integrated Approach Based on Computational Intelligence.

Georgina Stegmayer, Matias Gerard, Diego H. Milone

IEEE Comput. Intell. Mag., 2012

An evolutionary approach to metabolic pathways search.

Matias Fernando Gerard, Diego H. Milone, Georgina Stegmayer

Inteligencia Artif., 2012

2009

Métodos de agrupamiento no supervisado para la integración de datos genómicos y metabólicos de múltiples líneas de introgresión.

Diego H. Milone, Georgina Stegmayer, Matias Gerard, Laura Kamenetzky, Mariana G. Lopez, Fernando Carrari

Inteligencia Artif., 2009