Author

Dibyendu Bikash Seal

German Cancer Research CenterORCID 0000-0002-4802-0970Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Research Focus:benchmarking· 2 Approach:deep learning· 2 Research Focus:dimensionality reduction· 2 Research Focus:batch correction / integration· 1 Assay:CITE-seq· 1 Assay:multiome· 1 Assay:scRNA-seq· 1 Approach:statistical model· 1

Frequent Co-Authors

Chayan MaitraiD· 2 shared Rajat Kumar DeiD· 2 shared Vivek DasiD· 2 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

3 top collaborators · 3 mutual co-author links

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2 shared papersBioinformatics

Chayan MaitraORCID

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2 papers

Recent·Most cited

BioinformaticsJournal of Computational BiologyPeer-reviewedFeb 26, 2026

NeuroMDAVIS: Visualization of single-cell multi-omics data under deep learning framework

Chayan Maitra, Dibyendu Bikash Seal, Vivek Das, Rajat Kumar De

NeuroMDAVIS is a multi-omics visualization model that integrates multiple data modalities to generate low-dimensional embeddings preserving local and global structures, outperforming existing methods.

1 citation

multiomedeep learning

BioinformaticsFrontiers in Molecular BiosciencesPeer-reviewedMay 24, 2023

UMINT: Unsupervised Neural Network For Single Cell Multi-Omics Integration

Chayan Maitra, Dibyendu Bikash Seal, Vivek Das, Rajat Kumar De

UMINT is a novel unsupervised neural network for integrating single-cell multi-omics data, achieving better performance than existing methods on CITE-seq datasets.

12 citations

scRNA-seqCITE-seq