Author

Jeremy Bigness

Brown UniversityORCID 0000-0003-2871-1704Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:ChIP-seq· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Approach:experimental assay· 1 Approach:graph neural network· 1 Organism:human· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Erica LarschaniD· 2 shared Ritambhara SinghiD· 2 shared Jiaqi ZhangiD· 1 shared Shalin S. PateliD· 1 shared Xavier Loinaz· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 8 mutual co-author links

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2 shared papersBioinformatics

Erica LarschanORCID

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2 papers

Recent·Most cited

BioinformaticsBioinformaticsPeer-reviewedJun 15, 2024

scNODE: Generative Model for Temporal Single Cell Transcriptomic Data Prediction

Jiaqi Zhang, Erica Larschan, Jeremy Bigness, Ritambhara Singh

scNODE predicts single-cell gene expression at unobserved timepoints using a deep learning model combining VAE and ODEs, improving trajectory inference and perturbation analysis.

28 citationstop 5%

scRNA-seqdeep learning

𝕏 PostBluesky

BioinformaticsJournal of Computational BiologyPeer-reviewedMar 24, 2022

Integrating long-range regulatory interactions to predict gene expression using graph convolutional networks

Jeremy Bigness, Xavier Loinaz, Shalin S. Patel…·Ritambhara Singh

The paper introduces GC-MERGE, a graph convolutional model that integrates spatial genomic organization and histone modifications to predict gene expression and interpret regulatory factors.

26 citations

humanDNA methylation

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