Daniel Larremore

Daniel B. Larremore

Postdoctoral Fellow
Center for Communicable Disease Dynamics
Harvard T.H. Chan School of Public Health
Curriculum Vitae
Google Scholar Page
(gratuitous collaboration graph)


Software and Code

  • webweb
  • webweb is a free software tool, for creating interactive network visualizations in MATLAB that are viewable in your web browser. The network at the top of this page is an example of webweb, with some modifications. Downloads and information can be found on the webweb page with a full set of examples and code too. Source code, written in javascript and d3, are found on the downloads page. Learn more about d3 at d3js.org. If you modify this code or use it to make figures, let me know and I'll be happy to post a link to your publication here.
  • [Download webweb]
  • percoVIS icon
  • PercoVIS is a free software tool, created to visualize the process of percolation on a network. It was developed with much inspiration and feedback from my collaborator, Dane Taylor. It includes Erdos-Renyi and Adjacent Edge decision rules for link addition, as well as the Social Climber attachment model. Documentation about these processes can be found on the download page. If you are interested in a similar tool to visualize Kuramoto oscillators, please check out Sebastian Skardal's Synched software.
  • [Download PercoVIS]
  • biSBM
  • biSBM is free and open-source code, created to apply the method described in the paper "Efficiently inferring community structure in bipartite networks". The code finds communities in a bipartite network using a maximum-likelihood approach stochastic block model. The code requires MATLAB as well as a C++ compiler. Details, and the publication on which this code is based, can be found through the link below.
  • [Download biSBM]
  • MATLAB Codes
    • findNetworkComponents - take an undirected network adjacency matrix and return the number of components, their sizes, and their membership lists.
    • [MATLAB File Exchange]

Research Interests

  • Networks - I am interested in the development of mathematical and statistical methods to understand the structure and function of networks. This includes the dynamics of human populations, environment, economics, education, health, and disease. But it also includes block models, generative models, and other network descriptors. Collaborators for this work are Abigail Z. Jacobs, Leto Peel, Aaron Clauset, Sam Arbesman, Johan Ugander, Bailey Fosdick, and Joel Nishimura.
  • Malaria - I work with Caroline Buckee, and Aaron Clauset on the development of robust and principled methods to understand genetic recombination among a subset of genes of Plasmodium falciparum, the parasite that causes a majority of malaria deaths each year.
  • Neuronal Networks - I investigate the role of network topology on the dynamics of excitable systems. A nice example of an excitable system that can be understood in this light is a neuronal network—a network of brain cells—where excitations may be passed from cell to cell via electrochemical impulses. Collaborators for this work are Juan G. Restrepo, Woodrow L. Shew, Ed Ott, Marshall Y. Carpenter, and Francesco Sorrentino.

Some day, I want to write papers with Sebastian Skardal and Barry Z. Cynamon. I also like to collaborate often with Hans, the Clauset Lab coffee machine.

Journal Publications

  • 2015 "Ape origins of human malaria virulence genes"
  • Daniel B. Larremore, William R. Proto, Aaron Clauset, Sesh A. Sundararaman, Weimin Liu, Dorothy E. Loy, Paul M. Sharp, Beatrice H. Hahn, Julian C. Rayner*, and Caroline O. Buckee*.
  • [In Press at Nature Communications]
  • 2015 "Systematic inequality and hierarchy in faculty hiring networks"
  • Aaron Clauset, Samuel Arbesman, and Daniel B. Larremore, Science Advances. 1, e1400005.
  • [Science Advances] [code and data] [interactive data visualization]
  • 2015 "Immune characterization of P. falciparum parasites with a shared genetic signature in a region of decreasing transmission"
  • Amy K. Bei, Ababacar Diouf, Kazutoyo Miura, Daniel B. Larremore, Ulf Ribacke, Gregory Tullo, Eli L. Moss, Daniel E. Neafsey, Rachel F. Daniels, Amir E. Zeituni, Iguosadolo Nosamiefan, Sarah K. Volkman, Ambroise D. Ahouidi, Daouda Ndiaye, Tandakha Dieye, Souleymane Mboup, Caroline O. Buckee, Carole Long, and Dyann F. Wirth, Infection and Immunity 83(1), 276.
  • [PDF] [IAI]
  • 2014 "Efficiently inferring community structure in bipartite networks"
  • Daniel B. Larremore, Aaron Clauset, and Abigail Z. Jacobs, Physical Review E 90(1), 012805.
  • [PDF] [PRE] [code and data]
  • 2014 "Inhibition Causes Ceaseless Dynamics in Networks of Excitable Nodes"
  • Daniel B. Larremore, Woodrow L. Shew, Edward Ott, Francesco Sorrentino, and Juan G. Restrepo, Physical Review Letters 112, 138103.
  • [PDF] [PRL]
  • 2013 "A network approach to analyzing highly recombinant malaria parasite genes"
  • Daniel B. Larremore, Aaron Clauset, and Caroline O. Buckee. PLoS Computational Biology 9(10), e1003268.
  • [PDF] [PLoS Comp Bio] [interactive figures] [network and sequence data]
  • 2012 "Social Climber attachment in forming networks produces phase transition in a measure of connectivity"
  • Dane Taylor*, Daniel B. Larremore*. Physical Review E 86, 031140.
  • [PDF] [PRE]
  • 2012 "Statistical properties of avalanches in networks"
  • Daniel B. Larremore, Marshall Y. Carpenter, Edward Ott, and Juan G. Restrepo. Physical Review E 85, 066131.
  • [PDF] [PRE]
  • 2011 "Effects of network topology, transmission delays, and refractoriness on the response of coupled excitable systems to a stochastic stimulus"
  • Daniel B. Larremore, Woodrow L. Shew, Edward Ott, and Juan G. Restrepo. Chaos 21, 025117.
  • [PDF] [Chaos]
  • 2011 "Predicting criticality and dynamic range in complex networks: effects of topology"
  • Daniel B. Larremore, Woodrow L. Shew, and Juan G. Restrepo. Physical Review Letters 106, p. 058101.
  • [PDF] [PRL]

* denotes equal contribution.

Other Publications

  • 2014 Critical Dynamics in Complex Networks, chapter in Criticality in Neural Systems.
  • Daniel B. Larremore, Woodrow L. Shew, Juan G. Restrepo. Wiley, 365-392, 2014.
  • [Wiley]
  • 2012 "Progess Is Infectious"
  • Daniel E. Geer Jr., Daniel B. Larremore. IEEE Security & Privacy, 10(6), p. 94-95.
  • [PDF] [IEEE S&P]


Teaching and Workshops

Workshops and Guest Lecturing
  • University of Colorado at Boulder
  • 2014 Oct 9, CSCI 5352. Network Analysis and Modeling
  • 2013 Nov 5-7, PHYS 7810 / CHEM 6711 / MCDB 6400. Foundations of Quantitative Biology
  • HSPH summer nanocourse: Modeling Infectious Disease
  • 2014 July 24 and 27. [details]
  • AMS Mathematics Research Community
  • 2014 June 24-30, Network Science. [details]
  • Oxford Tropical Disease Network Meeting, Kilifi, Kenya
  • 2013 Oct 3, Network Analysis Workshop.

I am not doing any teaching at this time.
Previous courses are listed below. See my FCQ evaluations.

  • University of Colorado at Boulder
  • 2012 Spring APPM 2350, Calculus III (Instructor)
  • 2011 Fall APPM 2350, Calculus III (Instructor)
  • 2009 - 2010 Applied Mathematics Lead TA
  • 2009 Fall - APPM 1360, Calculus II (TA)
  • 2009 Spring - APPM 2360, Ordinary Differential Equations (TA)
  • 2008 Fall - APPM 2350, Calculus III (TA)
  • 2008 Summer - APPM 2350, Calculus III (TA)
  • 2008 Spring - APPM 2360, Ordinary Differential Equations (TA)
  • 2007 Fall - APPM 2350, Calculus III (TA)

Contact Details

Harvard School of Public Health
Center for Communicable Disease Dynamics
Department of Epidemiology
677 Huntington Avenue, Ste. 506
Boston, MA 02115