Francesco Faiola

4.1k citations
90 papers · 2.9k · h-index 31

Impact in

Papers in

Francesco Faiola

85 papers receiving 2.9k citations

Peers

Francesco Faiola
Comparison fields: 5 of 125
  • Health, Toxicology and Mutagenesis 788
  • Environmental Chemistry 332
  • Molecular Biology 1.6k
  • Developmental Neuroscience 86
  • Pollution 218
Replace Oswaldo Keith Okamoto with:
Oswaldo Keith Okamoto Brazil
Mohammed Abderrafi Benotmane Belgium
Pauliina Damdimopoulou Sweden
William Ka Fai Tse Japan
Xiaoyan Ding China
Mi Deng China
Yung‐Feng Lin Taiwan
Nancy Lan Guo United States
Chien‐Hung Chen Taiwan
Takahiko Sato Japan
Francesco Faiola relative to Oswaldo Keith Okamoto Brazil Oswaldo Keith Okamoto's profile →
Citations per field
00.5×2.6×
Oswaldo Keith Okamoto · 1×
Citations per year

Countries citing papers authored by Francesco Faiola

Since Specialization
Citations

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

Fields of papers citing papers by Francesco Faiola

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Francesco Faiola. 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 Francesco Faiola. The network helps show where Francesco Faiola may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 90 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013321
2 2008169
3 2005165
4 2011140
5 2020116
6 201393
7 201990
8 201287
9 201886
10 201772
11 201563
12 201862
13 200758
14 201957
15 201951
16 201750
17 201548
18 201447
19 202046
20 201545

About Francesco Faiola

Francesco Faiola is a scholar working on Molecular Biology, Health, Toxicology and Mutagenesis, Biomedical Engineering, Materials Chemistry and Pollution, having authored 90 papers that have together received 2.9k indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (26 papers), Effects and risks of endocrine disrupting chemicals (25 papers), Genomics and Chromatin Dynamics (9 papers), Microplastics and Plastic Pollution (8 papers), Per- and polyfluoroalkyl substances research (8 papers), CRISPR and Genetic Engineering (8 papers), Anesthesia and Neurotoxicity Research (7 papers) and Carcinogens and Genotoxicity Assessment (7 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (788 citations), Environmental Chemistry (332 citations), Molecular Biology (1.6k citations), Developmental Neuroscience (86 citations) and Pollution (218 citations). Francesco Faiola has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Nuoya Yin, Renjun Yang, Jianlong Wang, Ernest Martinez, Arven Saunders, Shengxian Liang, Shaojun Liang, Junjun Ding, Yuanliang Wang and Songqin Pan. Their work appears in journals such as Environmental Science & Technology, Journal of Hazardous Materials, Journal of Environmental Sciences, Environmental Pollution and Ecotoxicology and Environmental Safety.

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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