Author

Javier de Velasco Oriol

Tecnológico de MonterreyORCID 0000-0002-7556-245XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:GWAS summary statistics· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Edgar E. VallejoiD· 2 shared Antonio Martínez‐TorteyaiD· 1 shared Israel Alanis· 1 shared José G. Tamez‐PeñaiD· 1 shared Karol EstradaiD· 1 shared The Alzheimer’s Disease Neuroimaging Initiative· 1 shared Víctor TreviñoiD· 1 shared

Activity by Year

2019-2019 · peak 2/yr

Co-Author Collaboration Network

7 top collaborators · 13 mutual co-author links

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2 shared papersBioinformatics

Edgar E. VallejoORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintAug 13, 2019

Benchmarking machine learning models for the analysis of genetic data using FRESA.CAD Binary Classification Benchmarking

Javier de Velasco Oriol, Antonio Martínez‐Torteya, Víctor Treviño…·José G. Tamez‐Peña

The paper benchmarks machine learning models for genetic data analysis using FRESA.CAD Binary Classification Benchmarking, showing quantitative and qualitative advantages over existing tools.

3 citations

GWAS summary statisticsmachine learning (classical)

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BioinformaticsbioRxivPreprintMay 6, 2019

Predicting late-onset Alzheimer’s disease from genomic data using deep neural networks

Javier de Velasco Oriol, Edgar E. Vallejo, Karol Estrada, The Alzheimer’s Disease Neuroimaging Initiative

This study uses deep neural networks to predict late-onset Alzheimer’s disease from genetic variants, showing promise for clinical diagnosis.

1 citation

humanGWAS summary statistics

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