Author

Jhonny Rodriguez-Lopez

The Ohio State UniversityORCID 0009-0007-0637-8839Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:differential expression· 3 Organism:human· 3 Assay:spatial transcriptomics· 3 Research Focus:cell type annotation· 2 Assay:scRNA-seq· 2 Approach:statistical model· 2 Research Focus:clustering· 1 Approach:deep learning· 1

Frequent Co-Authors

Ahmed H. GhobashiiD· 3 shared Ana Lucia MoraiD· 3 shared Cankun WangiD· 2 shared Dongjun ChungiD· 2 shared Konstantin ShiloiD· 2 shared Lorena RosasiD· 2 shared Mauricio M. RojasiD· 2 shared Qin MaiD· 2 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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3 shared papersBioinformatics

Ahmed H. GhobashiORCID

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3 papers

Recent·Most cited

Molecular BiologybioRxivPreprintApr 10, 2026

Transcriptional and spatial profiling of fibroblasts from human lungs highlights CTHRC1+ cells as fibrogenic signaling hubs in fibrosis

Natalia Vanegas-Avendaño, H. Chen, Jack H. Wellmerling…·Mauricio M. Rojas

The paper integrates single-cell RNA sequencing and spatial transcriptomics to identify CTHRC1+ fibroblasts as key fibrogenic cells in IPF, showing how culture affects their transcriptional profile.

1 citation

humanscRNA-seq

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BioinformaticsbioRxivPreprintJul 1, 2025

Characterizing Cellular Heterogeneity and Transcriptomic Features of Senotype Using Deep Graph Representation Learning

Anjun Ma, Hao Cheng, Ahmed H. Ghobashi…·Qin Ma

This paper introduces DeepSAS, a deep graph framework to identify senescent cells and their associated genes, revealing cell-type-specific senescence features in aging and disease.

DOI 10.1101/2025.07.01.662364

humanscRNA-seq

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BioinformaticsbioRxivPreprintFeb 28, 2022

Defining transcriptomic niches in human fibrotic lung with multi-sample spatial transcriptomics analysis using the MAPLE algorithm

Hyeongseon Jeon, Carter Allen, N.D.P. Vanegas…·Dongjun Chung

The paper uses spatial transcriptomics and the MAPLE algorithm to analyze fibrotic lung tissue, identifying spatial biomarkers and fibrotic programs in IPF.

17 citations

humanspatial transcriptomics

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