Author

Min‐Gyoung Shin

Gladstone InstitutesORCID 0000-0001-8350-1334Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Cell Biology· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Research Focus:differential expression· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Reuben ThomasiD· 2 shared Alexander R. PicoiD· 1 shared Ce GaoiD· 1 shared Charlene Smith-GeateriD· 1 shared Chenyang JiangiD· 1 shared Chris Paiz· 1 shared Dan P. FelsenfeldiD· 1 shared David P. MaisoniD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersImmunology

Reuben ThomasORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

ImmunologybioRxivPreprintSep 13, 2026

Plasma Proteomic Profiling Identifies a Subset of HIV Elite Controllers with Inflammatory Profiles Resembling People Without HIV

Shane D. Falcinelli, David P. Maison, Isaac Avila-Vargas…·Michael J. Peluso

The paper identifies a subset of HIV elite controllers with proteomic profiles similar to uninfected individuals, associated with lower viral reservoirs and protective HLA alleles.

DOI 10.64898/2026.09.06.749753

humanproteomics

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Cell BiologyNeurobiology of DiseasePeer-reviewedApr 19, 2025

Intersecting impact of CAG repeat and Huntingtin knockout in stem cell-derived cortical neurons

Jennifer T. Stocksdale, Matthew Joseph Leventhal, Stephanie Lam…·Leslie Michels Thompson

This study compares the effects of HTT knockout and CAG repeat expansion in cortical neurons, identifying shared and distinct biological pathways involved in HD.

4 citations

humanbulk RNA-seq

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BioinformaticsBMC GenomicsPeer-reviewedNov 25, 2023

Using Published Pathway Figures in Enrichment Analysis and Machine Learning

Min‐Gyoung Shin, Alexander R. Pico

This paper introduces PFOCR, a pathway database derived from published figures, and demonstrates its utility in cancer subtype and grade prediction.

12 citations

statistical modelmachine learning (classical)

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