A. C. Monster

39 total papers · 998 total citations
33 papers, 720 citations indexed

About

A. C. Monster is a scholar working on Cancer Research, Health, Toxicology and Mutagenesis and Spectroscopy. According to data from OpenAlex, A. C. Monster has authored 33 papers receiving a total of 720 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Cancer Research, 6 papers in Health, Toxicology and Mutagenesis and 6 papers in Spectroscopy. Recurrent topics in A. C. Monster's work include Carcinogens and Genotoxicity Assessment (7 papers), Advanced Chemical Sensor Technologies (6 papers) and Analytical Chemistry and Chromatography (6 papers). A. C. Monster is often cited by papers focused on Carcinogens and Genotoxicity Assessment (7 papers), Advanced Chemical Sensor Technologies (6 papers) and Analytical Chemistry and Chromatography (6 papers). A. C. Monster collaborates with scholars based in Netherlands, United States and Belgium. A. C. Monster's co-authors include Sanja Kežić, Frederik A. de Wolff, H K Wilson, Maarten M. Verberk, Sandrine Micallef, Frédéric Y. Bois, Weihsueh A. Chiu, Joop M. Houtkooper, Jacob Krüse and H. Veulemans and has published in prestigious journals such as IEEE Transactions on Biomedical Engineering, Toxicology and Applied Pharmacology and Toxicological Sciences.

In The Last Decade

A. C. Monster

33 papers receiving 643 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
A. C. Monster	307	284	106	94	86	33	720
P. O. Droz	280 0.9×	399 1.4×	81 0.8×	105 1.1×	45 0.5×	42	859
Andreas Czich	272 0.9×	172 0.6×	170 1.6×	53 0.6×	289 3.4×	30	863
Ulrike Bernauer	222 0.7×	274 1.0×	176 1.7×	46 0.5×	180 2.1×	40	848
Joel P. Bercu	198 0.6×	198 0.7×	53 0.5×	39 0.4×	152 1.8×	45	715
Marianne Nordqvist	261 0.9×	219 0.8×	132 1.2×	44 0.5×	113 1.3×	23	703
H. Ohtsuji	300 1.0×	204 0.7×	147 1.4×	43 0.5×	79 0.9×	15	624
Kaija Pekari	403 1.3×	421 1.5×	65 0.6×	60 0.6×	85 1.0×	29	737
Susanne Glowienke	236 0.8×	171 0.6×	41 0.4×	35 0.4×	136 1.6×	28	694
G. M�ller	237 0.8×	171 0.6×	142 1.3×	32 0.3×	79 0.9×	23	703
Jaroslav Mráz	249 0.8×	164 0.6×	156 1.5×	37 0.4×	206 2.4×	62	747

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-authorship network of co-authors of A. C. Monster

This figure shows the co-authorship network connecting the top 25 collaborators of A. C. Monster. A scholar is included among the top collaborators of A. C. Monster based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with A. C. Monster. A. C. Monster is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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