Author

David Belanger

Google (United States)ORCID 0000-0001-9673-1630Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Assay:DNA methylation· 1 Research Focus:eQTL / molecular QTL mapping· 1 Research Focus:fine-mapping· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:protein sequence· 1

Frequent Co-Authors

Maxwell L. BileschiiD· 2 shared Brandon CarteriD· 1 shared Cory Y. McLeaniD· 1 shared David R. KelleyiD· 1 shared Drew BryantiD· 1 shared Jamie SmithiD· 1 shared Jasper Snoek· 1 shared Lucy J. ColwelliD· 1 shared

Activity by Year

2018-2019 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBioinformatics

Maxwell L. BileschiORCID

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2 papers

Recent·Most cited

BioinformaticsJournal of Computational BiologyPeer-reviewedDec 24, 2019

Critiquing Protein Family Classification Models Using Sufficient Input Subsets

Brandon Carter, Maxwell L. Bileschi, Jamie Smith…·Lucy J. Colwell

The paper critiques protein family classification models by identifying sufficient input subsets to understand their decision-making criteria.

10 citations

protein sequencestatistical model

GenomicsGenome ResearchPeer-reviewedMay 1, 2018

Sequential regulatory activity prediction across chromosomes with convolutional neural networks

David R. Kelley, Yakir Reshef, Maxwell L. Bileschi…·Jasper Snoek

The paper develops a machine learning system using convolutional neural networks to predict cell type-specific epigenetic and transcriptional profiles from DNA sequence, showing alignment with eQTL causal variants.

538 citations

humanDNA methylation