Author

R. Shanmugam

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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Scientific Communication & Education· 2 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Approach:experimental assay· 1 Organism:human· 1 Assay:spatial transcriptomics· 1 Approach:statistical model· 1

Frequent Co-Authors

G. Ledlow· 2 shared K. P. Singh· 2 shared A. Aiderus· 1 shared A. W.-C. Koh· 1 shared A. Y.-F. Chung· 1 shared B. K. P. Goh· 1 shared D. H. H. Ying· 1 shared G. B. Chen· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersScientific Communication & Education

G. Ledlow

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Multi-region spatial transcriptome analysis reveals cellular networks and pathways associated with hepatocellular carcinoma recurrence

A. Aiderus, P. V. Seshachalam, K. Idzham, M. Caldez, R. Shanmugam, I. N. Sari, D. H. H. Ying, S. L. Chong, K. Sekar, S. C. Chew, G. B. Chen, A. Y.-F. Chung, P. C. Cheow, J. H. Kam, A. W.-C. Koh, , P. K. H. Chow

This study uses spatial transcriptomics to analyze HCC tumor sectors and identifies endothelial cell enrichment and ligand-receptor interactions linked to disease recurrence.

bioRxiv · Jul 26, 2023 · PreprintCancer Biology

Heterogeneity versus the COVID-19 Pandemic

R. Shanmugam, G. Ledlow, K. P. Singh

This paper defines heterogeneity and examines its role in COVID-19 contagion using data from the Diamond Princess Cruise ship, suggesting testing protocols could improve safety in similar settings.

bioRxiv · Jan 6, 2021 · PreprintScientific Communication & Education

Predicting COVID-19 cases with unknown homogeneous or heterogeneous resistance to infectivity

R. Shanmugam, G. Ledlow, K. P. Singh

This paper introduces a refined inverse binomial model to predict COVID-19 cases after family gatherings, showing it better fits data with varying variance compared to traditional models.

bioRxiv · Dec 21, 2020Scientific Communication & Education