Steven G. Carmella

10.5k citations
190 papers · 7.8k indexed · h-index 51

Steven G. Carmella

185 papers receiving 7.6k citations

Peers

Steven G. Carmella
Comparison fields: 5 of 157
  • Health, Toxicology and Mutagenesis 1.8k
  • Physiology 3.1k
  • Cancer Research 1.7k
  • Biochemistry 453
  • Pharmacology 429
Replace Sharon E. Murphy with:
Sharon E. Murphy United States
Gerhard Scherer Germany
Irina Stepanov United States
Ellen Kampman Netherlands
D. Hoffmann United States
Adrian A. Franke United States
Janne Hukkanen Finland
Jakob Linseisen Germany
Sabina Sieri Italy
Kei Nakachi Japan
Steven G. Carmella relative to Sharon E. Murphy United States Sharon E. Murphy's profile →
Citations per field
00.5×
Sharon E. Murphy · 1×
Citations per year

Countries citing papers authored by Steven G. Carmella

Since Specialization
Citations

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

Fields of papers citing papers by Steven G. Carmella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Steven G. Carmella. 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 Steven G. Carmella. The network helps show where Steven G. Carmella may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 201919
3 201744
4 201627
5 201625
6 20163
7 201615
8 201439
9 2014103
10 201432
11 201335
12 201244
13 2011102
14 200956
15
r-1,t-2,3,c-4-Tetrahydroxy-1,2,3,4-tetrahydrophenanthrene in Human Urine
20031
16
r-1,t-2,3,c-4-Tetrahydroxy-1,2,3,4-tetrahydrophenanthrene in human urine: a potential biomarker for assessing polycyclic aromatic hydrocarbon metabolic activation.
200360
17 199618
18
Uptake and metabolism of carcinogenic levels of tobacco-specific nitrosamines by Sudanese snuff dippers.
199451
19 199351
20 199382

About Steven G. Carmella

Steven G. Carmella is a scholar working on Cancer Research, Physiology and Health, Toxicology and Mutagenesis, having authored 190 papers that have together received 7.8k indexed citations. Recurring topics across this work include Smoking Behavior and Cessation (69 papers), Genomics, phytochemicals, and oxidative stress (60 papers), Carcinogens and Genotoxicity Assessment (55 papers), Glutathione Transferases and Polymorphisms (27 papers), Air Quality and Health Impacts (20 papers), Indoor Air Quality and Microbial Exposure (17 papers), Synthesis and Biological Evaluation (17 papers) and Nicotinic Acetylcholine Receptors Study (14 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (1.8k citations), Physiology (3.1k citations) and Cancer Research (1.7k citations). Steven G. Carmella has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Stephen S. Hecht, Sharon E. Murphy, Dorothy K. Hatsukami, Shobha A. Akerkar, Menglan Chen, Irina Stepanov, Chap T. Le, Joni Jensen, Shaomei Han and Pramod Upadhyaya. Their work appears in journals such as New England Journal of Medicine, Accounts of Chemical Research and PLoS ONE.

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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