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John Spouge, MD, PhD

About

Picture of John Spouge, MD, PhD

John Spouge, MD, PhD

Senior Investigator, Computational Biology Branch, NCBI

My research interests flow from my technical mathematical skills, particularly in sequence statistics, which I apply to solve specific problems with broad biological pertinence. For example, I have used in vitro or animal trial data to model the efficacy of HIV therapies in patients. I have also analyzed data for botanists and mycologists in International Barcode Consortium Working Groups to help them decide on DNA barcodes for plants and fungi/

Contact Information

Building 38A, 8600 Rockville Pike MSC 6075 Bethesda, MD 20894

Tel: (301) 402-9310

spouge@nih.gov

Research Interests

Presently, I am attempting to understand the genetics of HIV or other retroviruses immediately after infection of a single host. Animal trials using infection as an end-point might not have enough sensitivity to detect subtle reductions in virulence, so my specific practical goal is to develop genetic criteria for detecting when a therapy has reduced virulence. I am also examining applications of exact k-mer matching to taxonomic identification of unknown biological samples.

Publications

Martín MP, Daniëls PP, Erickson D, Spouge JL. Figures of merit and statistics for detecting faulty species identification with DNA barcodes: A case study in Ramaria and related fungal genera. PLoS One. 2020;15(8):e0237507. doi: 10.1371/journal.pone.0237507. eCollection 2020. PubMed PMID: 32813726; PubMed Central PMCID: PMC7437900.

Patel V, Spouge JL. Estimating the basic reproduction number of a pathogen in a single host when only a single founder successfully infects. PLoS One. 2020;15(1):e0227127. doi: 10.1371/journal.pone.0227127. eCollection 2020. PubMed PMID: 31923263; PubMed Central PMCID: PMC6953795.

Hoang MTV, Irinyi L, Chen SCA, Sorrell TC, Meyer W. Dual DNA Barcoding for the Molecular Identification of the Agents of Invasive Fungal Infections. Front Microbiol. 2019;10:1647. doi: 10.3389/fmicb.2019.01647. eCollection 2019. PubMed PMID: 31379792; PubMed Central PMCID: PMC6657352.

Manzourolajdad A, Spouge JL. Structural prediction of RNA switches using conditional base-pair probabilities. PLoS One. 2019;14(6):e0217625. doi: 10.1371/journal.pone.0217625. eCollection 2019. PubMed PMID: 31188853; PubMed Central PMCID: PMC6561571.

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