C. Brandon Ogbunu is an Assistant Professor in the Department of Ecology and Evolutionary Biology at Brown University. He is an evolutionary systems biologist, and uses experimental evolution, mathematical modeling, and computational biology to better understand the underlying causes and consequences of disease, across scales: from the biophysics of proteins involved in drug resistance to the social determinants underlying disease. In doing so, he aims to develop theory that enriches our understanding of the evolutionary and ecological underpinnings of disease, while contributing to practical solutions for clinical medicine and public health. Read more about his research and activities here:
|Miller-Dickson, Miles, Meszaros, Victor A., Baffour-Awuah Junior, Francis, Almagro-Moreno, Salvador, Ogbunugafor, C. Brandon Waterborne, abiotic and other indirectly transmitted (W.A.I.T.) infections are defined by the dynamics of free-living pathogens and environmental reservoirs. 2019;|
|Ogbunugafor, C. Brandon, Guerrero, Rafael F, Eppstein, Margaret J. Genotypic context modulates fitness landscapes: Effects on the speed and direction of evolution for antimicrobial resistance. . 2018;|
|Ogbunugafor CB, Hartl DL A New Take on John Maynard Smith's Concept of Protein Space for Understanding Molecular Evolution.. PLOS Computational Biology. 2016; 12 (10) : e1005046.|
|Ogbunugafor CB, Hartl D A pivot mutation impedes reverse evolution across an adaptive landscape for drug resistance in Plasmodium vivax.. Malaria journal. 2016; 15 : 40.|
|Ogbunugafor, C. Brandon, Wylie, C. Scott, Diakite, Ibrahim, Weinreich, Daniel M., Hartl, Daniel L. Adaptive Landscape by Environment Interactions Dictate Evolutionary Dynamics in Models of Drug Resistance.. PLOS Computational Biology. 2016; 12 (1) : e1004710.|
|Ogbunugafor CB, Eppstein MJ Competition along trajectories governs adaptation rates towards antimicrobial resistance.. Nature ecology & evolution. 2016; 1 (1) : 7.|
|Ogbunugafor CB, Robinson SP OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems.. PLoS ONE. 2016; 11 (6) : e0156844.|
|Wasik BR, Bhushan A, Ogbunugafor CB, Turner PE Delayed transmission selects for increased survival of vesicular stomatitis virus.. Evolution. 2015; 69 (1) : 117-25.|
|Ogbunugafor CB, Basu S, Morales NM, Turner PE Combining mathematics and empirical data to predict emergence of RNA viruses that differ in reservoir use.. Philosophical Transactions of the Royal Society B: Biological Sciences. 2010; 365 (1548) : 1919-30.|
|Ogbunugafor CB, Pease JB, Turner PE On the possible role of robustness in the evolution of infectious diseases.. Chaos: An Interdisciplinary Journal of Nonlinear Science. 2010; 20 (2) : 026108.|
|Ogbunugafor CB, McBride RC, Turner PE Predicting virus evolution: the relationship between genetic robustness and evolvability of thermotolerance.. Cold Spring Harbor Symposia on Quantitative Biology. 2009; 74 : 109-18.|
|Ogbunugafor CB, Sumba L Behavioral evidence for the existence of a region-specific oviposition cue in Anopheles gambiae s.s.. Journal of vector ecology : journal of the Society for Vector Ecology. 2008; 33 (2) : 321-4.|
|Sumba LA, Ogbunugafor CB, Deng AL, Hassanali A Regulation of oviposition in Anopheles gambiae s.s.: role of inter- and intra-specific signals.. Journal of chemical ecology. 2008; 34 (11) : 1430-6.|
|McBride RC, Ogbunugafor CB, Turner PE Robustness promotes evolvability of thermotolerance in an RNA virus.. BMC evolutionary biology. 2008; 8 : 231.|
|Omlin FX, Carlson JC, Ogbunugafor CB, Hassanali A Anopheles gambiae exploits the treehole ecosystem in western Kenya: a new urban malaria risk?. The American Journal of Tropical Medicine and Hygiene. 2007; 77 (6 Suppl) : 264-9.|
|Ogbunugafor CB On reductionism in biology: pillars, leaps, and the naïve behavioral scientist.. The Yale journal of biology and medicine. 2004; 77 (3-4) : 101-9.|
The Ogbunu Lab studies the forces that influence and craft disease across scales, from the population level (“large”) to the molecular level (“small”).
At each scale, we ask questions that are simultaneously relevant for the study of disease (and potential treatment and prevention regimen), and for theoretical questions in evolutionary biology, ecology, and information theory. In this sense, we aim to establish a bi-directional relationship between theory and disease: theory allows us to ask important questions about disease, and disease systems provide great models for asking basic questions about how systems (biological, informational, and artificial) evolve and change.
1.“Small” scale (molecular): I study agents of disease, mostly (but not exclusively) microbes, and aim to understand (at the molecular level) the evolutionary and ecological determinants that drive disease.
2.“Large” scale (Eco-Population): How does the interaction between pathogens, hosts and the environment influence the dynamics of infection? By modeling these dynamics, can we learn anything that might allow us to better prevent or intervene in epidemics? What social phenomenon (behavioral, cultural, economic, social) are influencing the ecology of disease?
Co-Principal Investigator. “Using Biophysical Protein Models to Map Genetic Variation to Phenotypes.” National Science Foundation RII Track-2 FEC. (2017–2021)
Former Co-Principal Investigator. “Quantitative & Evolutionary STEM Training (QUEST): An Integrative Training Program to Solve Environmental and Global Health Problems.” National Science Foundation NRT. (2017–2022)
Former Co-Investigator. “Translational Global Infectious Disease Research Center.” National Institutes of Health. COBRE. University of Vermont (2018-2023).
|Postdoctoral Associate||Harvard university , Population Genetics||2013-2016||Cambridge, MA|
Society for the Study of Evolution (SSA)
International Society for Evolution Medicine and Public Health