James E. Johndrow

1.5k citations
24 papers · 923 · h-index 10

Impact in

  • Immunology top 10%
    • interferon and immune responses
    • Immune Response and Inflammation
    • Tuberculosis Research and Epidemiology

Papers in

James E. Johndrow

23 papers receiving 911 citations

Peers

James E. Johndrow
Comparison fields: 5 of 118
  • Immunology 323
  • Infectious Diseases 220
  • Cell Biology 155
  • Statistics and Probability 54
  • Epidemiology 197
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Citations per year

Countries citing papers authored by James E. Johndrow

Since Specialization
Citations

This map shows the geographic impact of James E. Johndrow'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 James E. Johndrow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James E. Johndrow more than expected).

Fields of papers citing papers by James E. Johndrow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James E. Johndrow. 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 James E. Johndrow. The network helps show where James E. Johndrow may publish in the future.

Co-authors

The 25 scholars most cited alongside James E. Johndrow, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with James E. Johndrow Line = papers co-authored together James E. Johndrow links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007324
2 2006253
3 2006117
4 200753
5 200523
6
Scalable Approximate MCMC Algorithms for the Horseshoe Prior
202022
7 201919
8 200418
9 200614
10 202210
11 20209
12 20159
13
Diagonal Orthant Multinomial Probit Models
20138
14 20188
15
Error bounds for Approximations of Markov chains
20175
16
Sisyphus, the Drosophila myosin XV homolog, traffics within filopodia transporting key sensory and adhesion cargos
20085
17 20175
18 20215
19 20224
20 20184

About James E. Johndrow

James E. Johndrow is a scholar working on Statistics and Probability, Artificial Intelligence, Cell Biology, Modeling and Simulation and Molecular Biology, having authored 24 papers that have together received 923 indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (5 papers), Bayesian Methods and Mixture Models (5 papers), Cellular Mechanics and Interactions (4 papers), COVID-19 epidemiological studies (4 papers), Statistical Methods and Bayesian Inference (3 papers), Statistical Methods and Inference (3 papers), Cytokine Signaling Pathways and Interactions (2 papers) and COVID-19 Pandemic Impacts (2 papers). The work is most often cited by research in Immunology (323 citations), Infectious Diseases (220 citations), Cell Biology (155 citations), Statistics and Probability (54 citations) and Epidemiology (197 citations). James E. Johndrow has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Sarah A. Stanley, Paolo Manzanillo, Jeffery S. Cox, Susan M. Parkhurst, Fabiana S. Machado, André Báfica, Charles N. Serhan, Alexandra Dias, Júlio Aliberti and Lísia Esper. Their work appears in journals such as Biometrika, Journal of Machine Learning Research, Nature Medicine, Biochemistry and Cell Biology and Journal of the American Chemical Society.

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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