Author

Ashish Kumar Pathak

Florida Agricultural and Mechanical UniversityORCID 0000-0003-2114-396XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Microbiology· 1

Signature Assays, Organisms & Methods

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Assay:metagenomics· 2 Approach:statistical model· 2 Organism:Arabidopsis· 1 Assay:bulk RNA-seq· 1 Research Focus:database / resource· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1

Frequent Co-Authors

Ashvini ChauhaniD· 2 shared Bobby Edwards· 1 shared Christian ChukwujinduiD· 1 shared Daris P Simon· 1 shared Devin Alvarez· 1 shared Mamta JunejaiD· 1 shared Navya Kommu· 1 shared Paul StothardiD· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 15 mutual co-author links

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2 shared papersMicrobiology

Ashvini ChauhanORCID

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3 papers

Recent·Most cited

MicrobiologybioRxivPreprintSep 10, 2025

Bioprospecting Native Oleaginous Microalgae for Wastewater Nutrient Remediation and Lipid Production

Bobby Edwards, Daris P Simon, Ashish Kumar Pathak…·Ashvini Chauhan

This study identifies native microalgal consortia from wastewater that efficiently remove nutrients and accumulate lipids, showing potential for biofuel production and wastewater treatment.

DOI 10.1101/2025.09.10.675442

metagenomicsexperimental assay

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BioinformaticsbioRxivPreprintOct 20, 2023

Metagenome Assembled Genomes (MAG) Facilitate a Better Understanding of Microbially-mediated Heavy Metal Resistance in Soils from a Former Nuclear Materials Production Facility

Navya Kommu, Paul Stothard, Christian Chukwujindu…·Ashvini Chauhan

The paper uses metagenome-assembled genomes (MAGs) to study microbially-mediated heavy metal resistance in soils from a former nuclear materials facility.

DOI 10.1101/2023.10.20.563326

metagenomicsstatistical model

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BioinformaticsbioRxivPreprintJun 19, 2020

Shortlisting genes important in seed maturation by principal component analysis of gene expression data

Ashish Kumar Pathak, Ridhima Singla, Mamta Juneja, Rakesh Tuli

The paper uses principal component analysis to identify functionally important genes in Arabidopsis seed development without relying on gene annotations.

3 citations

Arabidopsisbulk RNA-seq

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