Author

Chandra Mohan

University of HoustonORCID 0000-0001-7896-5740Unclaimed 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:clustering· 1 Research Focus:differential expression· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:proteomics· 1 Assay:scRNA-seq· 1 Approach:statistical model· 1

Frequent Co-Authors

Anto Sam Crosslee Louis Sam TitusiD· 1 shared Dee Zhang· 1 shared Gabby Lea· 1 shared Hong‐Long JiiD· 1 shared Jiwang ZhangiD· 1 shared Kamala VanarsaiD· 1 shared Laura L. KothiD· 1 shared Marc A. JudsoniD· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperBioinformatics

Anto Sam Crosslee Louis Sam TitusORCID

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2 papers

Recent·Most cited

Molecular BiologybioRxivPreprintOct 14, 2025

New proteomic biomarkers identified in plasma extracellular vesicles in sarcoidosis: a case-control matched study

Nan Miles Xi, Gabby Lea, Runzhen Zhao…·Hong‐Long Ji

This study identifies 97 plasma extracellular vesicle proteins as biomarkers for sarcoidosis using proteomics and machine learning, with 13 showing high diagnostic accuracy.

DOI 10.1101/2025.10.14.682425

humanproteomics

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BioinformaticsbioRxivPreprintDec 20, 2020

Polaratio: A magnitude-contingent monotonic correlation metric and its improvements to scRNA-seq clustering

Victor C. Wang, Pietro Antonio Cicalese, Anto Sam Crosslee Louis Sam Titus, Chandra Mohan

The paper introduces Polaratio, a new correlation metric for scRNA-seq data, and shows it improves clustering accuracy on 5 out of 7 datasets.

1 citation

scRNA-seqstatistical model

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