John Molitor

4.8k citations
62 papers · 3.7k · h-index 28

Impact in

Papers in

    • Air Quality and Health Impacts 24
    • Climate Change and Health Impacts 3
    • Genetic Associations and Epidemiology 10
    • Genetic Mapping and Diversity in Plants and Animals 4

John Molitor

59 papers receiving 3.6k citations

Peers

John Molitor
Comparison fields: 5 of 163
  • Health, Toxicology and Mutagenesis 835
  • Aging 65
  • Statistics and Probability 486
  • Genetics 889
  • Modeling and Simulation 44
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Citations per field
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Citations per year

Countries citing papers authored by John Molitor

Since Specialization
Citations

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

Fields of papers citing papers by John Molitor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John Molitor. 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 John Molitor. The network helps show where John Molitor may publish in the future.

Co-authors

The 25 scholars most cited alongside John Molitor, 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 John Molitor Line = papers co-authored together John Molitor links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003798
2 2005378
3 2014349
4 2008275
5 2011161
6 2009137
7 2010127
8 200481
9 202081
10 200380
11 201373
12 200871
13 202171
14 201666
15 200364
16 201562
17 200461
18 201153
19 200751
20 201750

About John Molitor

John Molitor is a scholar working on Health, Toxicology and Mutagenesis, Genetics, Statistics and Probability, Obstetrics and Gynecology and Public Health, Environmental and Occupational Health, having authored 62 papers that have together received 3.7k indexed citations. Recurring topics across this work include Air Quality and Health Impacts (24 papers), Genetic Associations and Epidemiology (10 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers), Environmental Justice and Health Disparities (4 papers), Maternal Mental Health During Pregnancy and Postpartum (3 papers), Statistical Methods in Epidemiology (3 papers), Climate Change and Health Impacts (3 papers) and Bayesian Methods and Mixture Models (3 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (835 citations), Aging (65 citations), Statistics and Probability (486 citations), Genetics (889 citations) and Modeling and Simulation (44 citations). John Molitor has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Paul Marjoram, Simon Tavaré, Vincent Plagnol, Carmen J. Marsit, Eugene Andres Houseman, Duncan C. Thomas, Michael Jerrett, Sylvia T. Richardson, Michail Papathomas and Keyan Zhao. Their work appears in journals such as Environment International, Environmental Health Perspectives, Environmental Research, PLoS Genetics and JAMA Network Open.

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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