Author

Lucas F. daSilva

Harvard UniversityORCID 0000-0002-1722-0611Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Approach:deep learning· 2 Assay:DNA methylation· 2 Research Focus:gene regulatory network inference· 2 Organism:human· 2 Research Focus:variant effect prediction· 2 Research Focus:benchmarking· 1 Assay:ChIP-seq· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Aaron WenteleriD· 1 shared Ana Carolina TahiraiD· 1 shared Aniketh Janardhan ReddyiD· 1 shared Cameron Smith· 1 shared Cesar Miguel Valdez CordovaiD· 1 shared Emily S. W. WongiD· 1 shared Lithin Karmel Louis· 1 shared Luca PinelloiD· 1 shared

Activity by Year

2019-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperSynthetic Biology

Aaron WentelerORCID

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2 papers

Recent·Most cited

Synthetic BiologybioRxivPreprintFeb 1, 2024

DNA-Diffusion: Leveraging Generative Models for Controlling Chromatin Accessibility and Gene Expression via Synthetic Regulatory Elements

Lucas F. daSilva, Simon Senan, Zain Munir Patel…·Luca Pinello

DNA-Diffusion uses diffusion models to generate cell type-specific regulatory DNA sequences that modulate chromatin accessibility and gene expression.

32 citations

humanDNA methylation

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BioinformaticsbioRxivPreprintDec 7, 2019

A Deep Learning approach predicts the impact of point mutations in intronic flanking regions on micro-exon splicing definition

Lucas F. daSilva, Ana Carolina Tahira, Vinícius Mesel, Sergio Verjovski‐Almeida

This paper develops a CNN model to predict how point mutations in intronic flanking regions affect micro-exon splicing, identifying conserved RNA-binding motifs as key predictors.

DOI 10.1101/868786

humanDNA methylation

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