Michael Famulare

3.6k total citations
20 papers, 472 citations indexed

About

Michael Famulare is a scholar working on Infectious Diseases, Cardiology and Cardiovascular Medicine and Modeling and Simulation. According to data from OpenAlex, Michael Famulare has authored 20 papers receiving a total of 472 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Infectious Diseases, 10 papers in Cardiology and Cardiovascular Medicine and 6 papers in Modeling and Simulation. Recurrent topics in Michael Famulare's work include Viral Infections and Immunology Research (10 papers), Viral gastroenteritis research and epidemiology (9 papers) and COVID-19 epidemiological studies (6 papers). Michael Famulare is often cited by papers focused on Viral Infections and Immunology Research (10 papers), Viral gastroenteritis research and epidemiology (9 papers) and COVID-19 epidemiological studies (6 papers). Michael Famulare collaborates with scholars based in United States, Australia and Bangladesh. Michael Famulare's co-authors include Eric Shea‐Brown, Joshua H. Goldwyn, Adrienne L. Fairhall, Guillaume Chabot‐Couture, Kevin McCarthy, Brian N. Lundstrom, Hao Hu, L. B. Sorensen, William J. Spain and Julijana Gjorgjieva and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Michael Famulare

19 papers receiving 446 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael Famulare United States 13 193 154 141 96 77 20 472
Haitao Song China 21 122 0.6× 152 1.0× 17 0.1× 37 0.4× 106 1.4× 56 1.2k
Fernando S. Borges Brazil 16 88 0.5× 10 0.1× 322 2.3× 232 2.4× 123 1.6× 56 719
Wayne P. London United States 10 52 0.3× 9 0.1× 87 0.6× 59 0.6× 14 0.2× 19 740
Pengxing Cao Australia 14 133 0.7× 13 0.1× 11 0.1× 14 0.1× 32 0.4× 29 558
Blake Caldwell United States 10 117 0.6× 6 0.0× 61 0.4× 6 0.1× 23 0.3× 17 389
Yingjie Bi China 9 53 0.3× 21 0.1× 15 0.1× 2 0.0× 92 1.2× 28 382
Valeria d’Andrea Italy 8 145 0.8× 5 0.0× 26 0.2× 25 0.3× 13 0.2× 17 285
Matthew J. Gonzales United States 14 547 2.8× 183 1.2× 7 0.0× 7 0.1× 20 0.3× 30 927
Maxim Mikheev United States 10 60 0.3× 50 0.3× 5 0.0× 7 0.1× 16 0.2× 19 831
Akiko Fukuda Japan 11 29 0.2× 7 0.0× 12 0.1× 73 0.8× 3 0.0× 39 419

Countries citing papers authored by Michael Famulare

Since Specialization
Citations

This map shows the geographic impact of Michael Famulare's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Famulare with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Famulare more than expected).

Fields of papers citing papers by Michael Famulare

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Famulare. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Famulare. The network helps show where Michael Famulare may publish in the future.

Co-authorship network of co-authors of Michael Famulare

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Famulare. A scholar is included among the top collaborators of Michael Famulare based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael Famulare. Michael Famulare is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wong, Wesley, Jillian Gauld, & Michael Famulare. (2023). From vaccine to pathogen: Modeling Sabin 2 vaccine virus reversion and evolutionary epidemiology in Matlab, Bangladesh. Virus Evolution. 9(2). vead044–vead044. 2 indexed citations
2.
Cohen, Jamie A., Robyn M. Stuart, Jasmina Panovska‐Griffiths, et al.. (2023). The changing health impact of vaccines in the COVID-19 pandemic: A modeling study. Cell Reports. 42(4). 112308–112308. 5 indexed citations
3.
Kerr, Cliff C., Robyn M. Stuart, Dina Mistry, et al.. (2022). Python vs. the pandemic: a case study in high-stakes software development. Proceedings of the Python in Science Conferences. 90–97.
4.
Brouwer, Andrew F., Marisa C. Eisenberg, Lester M. Shulman, et al.. (2022). The role of time-varying viral shedding in modelling environmental surveillance for public health: revisiting the 2013 poliovirus outbreak in Israel. Journal of The Royal Society Interface. 19(190). 20220006–20220006. 7 indexed citations
5.
Famulare, Michael, Wesley Wong, Rashidul Haque, et al.. (2021). Multiscale model for forecasting Sabin 2 vaccine virus household and community transmission. PLoS Computational Biology. 17(12). e1009690–e1009690. 4 indexed citations
6.
Kerr, Cliff C., Dina Mistry, Robyn M. Stuart, et al.. (2021). Controlling COVID-19 via test-trace-quarantine. Nature Communications. 12(1). 2993–2993. 73 indexed citations
7.
Jackson, Michael L., Gregory R. Hart, Denise J. McCulloch, et al.. (2021). Effects of weather-related social distancing on city-scale transmission of respiratory viruses: a retrospective cohort study. BMC Infectious Diseases. 21(1). 335–335. 13 indexed citations
8.
Valesano, Andrew L., Mami Taniuchi, William J. Fitzsimmons, et al.. (2020). The Early Evolution of Oral Poliovirus Vaccine Is Shaped by Strong Positive Selection and Tight Transmission Bottlenecks. Cell Host & Microbe. 29(1). 32–43.e4. 17 indexed citations
9.
Kroiss, Steve J., Jamal Ahmed, Muhammad Masroor Alam, et al.. (2018). Assessing the sensitivity of the polio environmental surveillance system. PLoS ONE. 13(12). e0208336–e0208336. 26 indexed citations
10.
Famulare, Michael, Christian Selinger, Kevin McCarthy, Philip A. Eckhoff, & Guillaume Chabot‐Couture. (2018). Assessing the stability of polio eradication after the withdrawal of oral polio vaccine. PLoS Biology. 16(4). e2002468–e2002468. 20 indexed citations
11.
Taniuchi, Mami, Michael Famulare, Khalequ Zaman, et al.. (2017). Community transmission of type 2 poliovirus after cessation of trivalent oral polio vaccine in Bangladesh: an open-label cluster-randomised trial and modelling study. The Lancet Infectious Diseases. 17(10). 1069–1079. 23 indexed citations
12.
Kroiss, Steve J., Michael Famulare, Hil Lyons, et al.. (2017). Evaluating cessation of the type 2 oral polio vaccine by modeling pre- and post-cessation detection rates. Vaccine. 35(42). 5674–5681. 10 indexed citations
13.
McCarthy, Kevin, Guillaume Chabot‐Couture, Michael Famulare, Hil Lyons, & Laina D. Mercer. (2017). The risk of type 2 oral polio vaccine use in post-cessation outbreak response. BMC Medicine. 15(1). 175–175. 18 indexed citations
14.
Famulare, Michael, Stewart T. Chang, Jane Iber, et al.. (2015). Sabin Vaccine Reversion in the Field: a Comprehensive Analysis of Sabin-Like Poliovirus Isolates in Nigeria. Journal of Virology. 90(1). 317–331. 50 indexed citations
15.
16.
Famulare, Michael. (2015). Has Wild Poliovirus Been Eliminated from Nigeria?. PLoS ONE. 10(8). e0135765–e0135765. 13 indexed citations
17.
Mease, Rebecca A., Michael Famulare, Julijana Gjorgjieva, William J. Moody, & Adrienne L. Fairhall. (2013). Emergence of Adaptive Computation by Single Neurons in the Developing Cortex. Journal of Neuroscience. 33(30). 12154–12170. 36 indexed citations
18.
19.
Goldwyn, Joshua H., et al.. (2011). Stochastic differential equation models for ion channel noise in Hodgkin-Huxley neurons. Physical Review E. 83(4). 41908–41908. 96 indexed citations
20.
Lundstrom, Brian N., Michael Famulare, L. B. Sorensen, William J. Spain, & Adrienne L. Fairhall. (2009). Sensitivity of firing rate to input fluctuations depends on time scale separation between fast and slow variables in single neurons. Journal of Computational Neuroscience. 27(2). 277–290. 40 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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