John S. House

1.7k citations
60 papers · 1.1k · 1 hit paper · h-index 19

Impact in

Papers in

John S. House

57 papers receiving 1.0k citations

John S. House's Hit Papers

Decoding the exposome: data science methodologies and implications in exposome-wide association studies (ExWASs) 2024 · 44 citations
440+1Years since publication10203040

Peers

John S. House
Comparison fields: 5 of 124
  • Health, Toxicology and Mutagenesis 260
  • Behavioral Neuroscience 22
  • Small Animals 44
  • Modeling and Simulation 27
  • Cancer Research 75
Replace Chi‐Chen Hong with:
Chi‐Chen Hong United States
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Autumn J. Bernal United States
Yu Han China
Lina Zhang China
Beth A. Vorderstrasse United States
Violeta Arsenescu United States
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Raimundo García del Moral Spain
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Citations per field
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Citations per year

Countries citing papers authored by John S. House

Since Specialization
Citations

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

Fields of papers citing papers by John S. House

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201865
2 202160
3 201957
4 201855
5 201754
6 201952
7 201648
8
Decoding the exposome: data science methodologies and implications in exposome-wide association studies (ExWASs)
Hit paper breakdown →
202444
9 201941
10 202237
11 201037
12 201736
13 200834
14 202026
15 201923
16 202222
17 202019
18 202219
19 202219
20 201518

About John S. House

John S. House is a scholar working on Molecular Biology, Health, Toxicology and Mutagenesis, Physiology, Public Health, Environmental and Occupational Health and Genetics, having authored 60 papers that have together received 1.1k indexed citations. Recurring topics across this work include Air Quality and Health Impacts (8 papers), Nutritional Studies and Diet (7 papers), Health, Environment, Cognitive Aging (6 papers), Molecular Biology Techniques and Applications (5 papers), Medical and Biological Ozone Research (4 papers), Asthma and respiratory diseases (4 papers), Gene expression and cancer classification (4 papers) and Climate Change and Health Impacts (4 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (260 citations), Behavioral Neuroscience (22 citations), Small Animals (44 citations), Modeling and Simulation (27 citations) and Cancer Research (75 citations). John S. House has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Fred A. Wright, Ivan Rusyn, Alison A. Motsinger‐Reif, Fabian A. Grimm, Weihsueh A. Chiu, Robert C. Smart, David M. Reif, Dereje D. Jima, Cathrine Hoyo and Yi‐Hui Zhou. Their work appears in journals such as Toxicological Sciences, Toxicology and Applied Pharmacology, ALTEX, PLoS ONE and Frontiers in Genetics.

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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