A. C. Monster

33 papers receiving 640 citations

Peers

A. C. Monster
Comparison fields: 5 of 84
  • Chemical Health and Safety 36
  • Health, Toxicology and Mutagenesis 284
  • Cancer Research 307
  • Pharmacology 106
  • Pharmaceutical Science 58
Replace P. O. Droz with:
P. O. Droz Switzerland
Kaija Pekari Finland
J.C. Ramsey United States
H. Ohtsuji Japan
Ulrike Bernauer Germany
G.L. Erexson United States
Borge M. Ulland United States
Jaroslav Mráz Czechia
U C Pozzani United States
Leung Hon-Wing United States
A. C. Monster relative to P. O. Droz Switzerland P. O. Droz's profile →
Citations per field
00.5×1.5×
P. O. Droz · 1×
Citations per year

Countries citing papers authored by A. C. Monster

Since Specialization
Citations

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

Fields of papers citing papers by A. C. Monster

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. C. Monster. 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 A. C. Monster. The network helps show where A. C. Monster may publish in the future.

Co-authors

The 24 scholars most cited alongside A. C. Monster, 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 A. C. Monster Line = papers co-authored together A. C. Monster links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 197970
2 197666
3 197945
4 199745
5 197538
6 198338
7 197936
8 200635
9 200131
10 197930
11 200026
12 199926
13 200021
14 200121
15 199319
16 197917
17 200116
18 200413
19 198813
20 198613

About A. C. Monster

A. C. Monster is a scholar working on Cancer Research, Health, Toxicology and Mutagenesis, Spectroscopy, Biomedical Engineering and Dermatology, having authored 33 papers that have together received 717 indexed citations. Recurring topics across this work include Carcinogens and Genotoxicity Assessment (7 papers), Advanced Chemical Sensor Technologies (6 papers), Analytical Chemistry and Chromatography (6 papers), Indoor Air Quality and Microbial Exposure (5 papers), Contact Dermatitis and Allergies (4 papers), Advancements in Transdermal Drug Delivery (4 papers), Analytical Chemistry and Sensors (4 papers) and Chemical Safety and Risk Management (4 papers). The work is most often cited by research in Chemical Health and Safety (36 citations), Health, Toxicology and Mutagenesis (284 citations), Cancer Research (307 citations), Pharmacology (106 citations) and Pharmaceutical Science (58 citations). A. C. Monster has collaborated with scholars based in Netherlands, United States and France. Frequent co-authors include Sanja Kežić, Frederik A. de Wolff, Maarten M. Verberk, H K Wilson, Frédéric Y. Bois, Weihsueh A. Chiu, Sandrine Micallef, Joop M. Houtkooper, Jacob Krüse and Jan N. M. Commandeur. Their work appears in journals such as International Archives of Occupational and Environmental Health, Occupational and Environmental Medicine, Occupational Medicine, Human & Experimental Toxicology and Toxicological Sciences.

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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