John Molitor

56 papers receiving 3.0k citations

Hit Papers

Markov chain Monte Carlo without likelihoods 2003 · 709 citations
7092003202620102018200400600

Peers

John Molitor
Comparison fields: 5 of 167
  • Health, Toxicology and Mutagenesis 894
  • Statistics and Probability 419
  • Speech and Hearing 236
  • Aging 58
  • Genetics 692
Replace William Navidi with:
William Navidi United States
Daniel Wartenberg United States
Fred A. Wright United States
Marc L. Serre United States
Thomas W. Yee New Zealand
Fuzhong Xue China
Brock C. Christensen United States
D. Stasinopoulos United Kingdom
Edward J. Bedrick United States
Olivier Thas Belgium
John Molitor relative to William Navidi United States William Navidi's profile →
Citations per field
00.5×8.3×
William Navidi · 1×
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 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Markov chain Monte Carlo without likelihoods
Hit paper breakdown →
2003709
2 2005343
3 2014304
4 2008255
5 2010116
6 200476
7 202072
8 200371
9 202167
10 201662
11 201362
12 201562
13 200358
14 200857
15 200456
16 201152
17 200748
18 201746
19 201043
20 200335

About John Molitor

John Molitor is a scholar working on Health, Toxicology and Mutagenesis, Transportation, Speech and Hearing, Aging and Statistics and Probability, having authored 59 papers that have together received 3.1k indexed citations. Recurring topics across this work include Air Quality and Health Impacts (25 papers), Climate Change and Health Impacts (20 papers), Genetic Associations and Epidemiology (7 papers), Bayesian Methods and Mixture Models (6 papers), Urban Transport and Accessibility (5 papers), Noise Effects and Management (5 papers), Genetic and phenotypic traits in livestock (4 papers) and Energy and Environment Impacts (4 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (894 citations), Statistics and Probability (419 citations), Speech and Hearing (236 citations), Aging (58 citations) and Genetics (692 citations). John Molitor has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Paul Marjoram, Vincent Plagnol, Simon Tavaré, E. Andrés Houseman, Carmen J. Marsit, Michael Jerrett, Duncan C. Thomas, Sylvia Richardson, Michail Papathomas and Keyan Zhao. Their work appears in journals such as Environment International, Environmental Health Perspectives, Environmental Research, JAMA Network Open and Human Heredity.

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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