Author

Jésus Antonio Motta

Université LavalORCID 0009-0006-7395-443XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:variant calling· 2 Research Focus:benchmarking· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:variant effect prediction· 1 Assay:whole-exome sequencing· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Carolina Fernandez· 1 shared Maria del Mar Motta· 1 shared Pedro David Gomez· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

3 top collaborators · 1 mutual co-author link

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1 shared paperBioinformatics

Carolina Fernandez

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintAug 20, 2026

A Semantic + Neuronal Approach to Predict Pathogenic Variants in DNA Sequences

Jésus Antonio Motta, Carolina Fernandez, Maria del Mar Motta

The paper presents a machine learning model that predicts pathogenic DNA variants using a semantic approach combined with CRF and BiLSTM, achieving state-of-the-art performance.

DOI 10.64898/2026.08.16.745093

whole-exome sequencingmachine learning (classical)

𝕏 PostBluesky

BioinformaticsInternational Conference on Advanced Information Technologies and Applications (ICAITA)Peer-reviewedJun 20, 2026

A Convolutional Deep Learning Approach to identify DNA Sequences for Gene Prediction

Jésus Antonio Motta, Pedro David Gomez

The paper presents a convolutional neural network for gene prediction using human genome sequences, achieving state-of-the-art results on genes associated with genetic disorders.

DOI 10.5121/csit.2026.1601104

humanwhole-genome sequencing

𝕏 PostBluesky