John Spouge, M.D., Ph.D.

Senior Investigator

Statistical Computational Biology Group


Building 38A, Room 6N603
8600 Rockville Pike
Bethesda, MD 20894


Research Topics

After experience elsewhere in the classical modeling of physical, chemical, and biological systems, particularly HIV infectivity assays, Dr. Spouge's research at NCBI has focused on sequence alignment and sequence structure statistics, with particular application to BLAST statistics and the detection of transcription binding factor motifs. Recently, he has contributed to the international effort to identify species with DNA barcodes, a field with applications to the conservation of species, the control of poaching, the protection against pests at customs, and the detection of consumer fraud by species substitution. Dr. Spouge's special interest is formulating and solving difficult mathematical problems that have important biological applications.


Dr. Spouge graduated from the University of British Columbia with a B.Sc. in Mathematics and an M.D., before obtaining a D. Phil. in Mathematics under John Hammersley at the University of Oxford. After a two-year post-doctoral fellowship at Los Alamos National Laboratory in T-10, the Theoretical Biology group, he came to the National Cancer Institute in 1985, and from there, to the National Center for Biotechnology Information (NCBI) in 1989.

Selected Publications

  1. Manzourolajdad A, Spouge JL. Structural prediction of RNA switches using conditional base-pair probabilities. PLoS One. 2019;14(6):e0217625.

  2. Spouge JL. An accurate approximation for the expected site frequency spectrum in a Galton-Watson process under an infinite sites mutation model. Theor Popul Biol. 2019;127:7-15.

  3. Gauran IIM, Park J, Lim J, Park D, Zylstra J, Peterson T, Kann M, Spouge JL. Empirical null estimation using zero-inflated discrete mixture distributions and its application to protein domain data. Biometrics. 2018;74(2):458-471.

  4. Silva JC, Egan A, Arze C, Spouge JL, Harris DG. A new method for estimating species age supports the coexistence of malaria parasites and their Mammalian hosts. Mol Biol Evol. 2015;32(5):1354-64.

  5. Sheetlin SL, Park Y, Frith MC, Spouge JL. Frameshift alignment: statistics and post-genomic applications. Bioinformatics. 2014;30(24):3575-82.

This page was last updated on August 22nd, 2019