Author

H. Lalchungnunga

National Cancer InstituteORCID 0000-0003-2718-6223Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Organism:human· 3 Research Focus:benchmarking· 2 Approach:deep learning· 2 Research Focus:differential expression· 2 Assay:DNA methylation· 2 Research Focus:gene regulatory network inference· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1

Frequent Co-Authors

Eytan RuppiniD· 2 shared Kenneth AldapeiD· 2 shared Omkar SinghiD· 2 shared Alejandro A. SchäfferiD· 1 shared Ananth HariiD· 1 shared Chris M. BaconiD· 1 shared Danh-Tai HoangiD· 1 shared Ed C. SchwalbeiD· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 23 mutual co-author links

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2 shared papersBioinformatics

Eytan RuppinORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintAug 12, 2026

Qombucha: Reconstructing unobserved progenitor methylation profiles reveals distinct developmental programs in glioblastoma

Xuan Cindy Li, H. Lalchungnunga, Ananth Hari…·S. Cenk Şahinalp

Qombucha infers unobserved progenitor methylation profiles in GBM, revealing subtype-specific developmental programs and improved subtype classification.

DOI 10.64898/2026.08.06.743400

humanDNA methylation

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Cancer BiologyBritish Journal of CancerPeer-reviewedOct 31, 2025

Deconvolution of cancer methylation patterns determines that altered methylation in cancer is dominated by a non-disease associated proliferation signal

H. Lalchungnunga, Hande Atasoy, Ed C. Schwalbe…·Gordon R. Strathdee

The paper deconvolves cancer methylation patterns to show that most methylation changes in B-cell cancers are proliferation-driven, not disease-specific, and identifies SLC22A15 as a novel tumour suppressor.

DOI 10.1038/s41416-025-03239-3

humanDNA methylation

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BioinformaticsCancer ResearchPeer-reviewedOct 30, 2025

Path2Omics: Enhanced transcriptomic and methylation prediction accuracy from tumor histopathology

Danh-Tai Hoang, Eldad David Shulman, Saugato Rahman Dhruba…·Eytan Ruppin

Path2Omics predicts gene expression and methylation from histopathology slides across 23 cancer types, outperforming previous models and showing effectiveness in predicting patient outcomes.

11 citationstop 5%

humanspatial transcriptomics

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