Author

Vijay K. Bhargava

University of British Columbia

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:dimensionality reduction· 2 Research Focus:gene regulatory network inference· 2 Approach:variational autoencoder· 2 Research Focus:benchmarking· 1 Assay:ChIP-seq· 1 Assay:DNA methylation· 1 Assay:Hi-C· 1

Frequent Co-Authors

Kevin Bradley DsouzaiD· 2 shared Maxwell W. LibbrechtiD· 2 shared Adam LiiD· 1 shared Alexandra Maslova· 1 shared Ediem Al-JiburyiD· 1 shared Matthias MerkenschlageriD· 1 shared

Activity by Year

2021-2022 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 12 mutual co-author links

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2 shared papersGenomics

Kevin Bradley DsouzaORCID

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2 papers

Recent·Most cited

Hi-C-LSTM: Learning representations of chromatin contacts using a recurrent neural network identifies genomic drivers of conformation

Kevin Bradley Dsouza, Alexandra Maslova, Ediem Al-Jibury, Matthias Merkenschlager, Vijay K. Bhargava, Maxwell W. Libbrecht

Hi-C-LSTM uses a recurrent neural network to learn low-dimensional representations of Hi-C data, enabling the identification of genomic elements that define chromatin conformation.

Nature Communications · Jun 28, 2022Peer-reviewedGenomics

Latent representation of the human pan-celltype epigenome through a deep recurrent neural network

Kevin Bradley Dsouza, Adam Li, Vijay K. Bhargava, Maxwell W. Libbrecht

This paper introduces Epi-LSTM, a deep LSTM autoencoder that creates a pan-celltype epigenomic representation, outperforming existing methods in most cell types and providing smoother genomic representations.

IEEE Transactions on Computational Biology and Bioinformatics · May 27, 2021Peer-reviewedBioinformatics