Fred Parham

1.9k citations
31 papers · 1.6k · h-index 20

Impact in

Papers in

Fred Parham

30 papers receiving 1.5k citations

Peers

Fred Parham
Comparison fields: 5 of 106
  • Health, Toxicology and Mutagenesis 758
  • Developmental Neuroscience 86
  • Small Animals 229
  • Cancer Research 158
  • Computational Theory and Mathematics 96
Replace Ulrike Hübenthal with:
Ulrike Hübenthal Germany
Kelly J. Chandler United States
Tamara L. Tal United States
Kristen Ryan United States
Dana L. Shuey United States
Julia Tigges Germany
Jill A. Franzosa United States
Ram Ramabhadran United States
C.E. van den Brink Netherlands
Nikolai Leonidovitch Chepelev Canada
Fred Parham relative to Ulrike Hübenthal Germany Ulrike Hübenthal's profile →
Citations per field
00.5×2×4×6×7.4×
Ulrike Hübenthal · 1×
Citations per year

Countries citing papers authored by Fred Parham

Since Specialization
Citations

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

Fields of papers citing papers by Fred Parham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019223
2 2000220
3 2018177
4 2016117
5 200890
6 199782
7 201776
8 200272
9 201872
10 202066
11 201846
12 199638
13 200436
14 200935
15 201830
16 200423
17 199822
18 201621
19 200420
20 200920

About Fred Parham

Fred Parham is a scholar working on Health, Toxicology and Mutagenesis, Small Animals, Cancer Research, Developmental Neuroscience and Molecular Biology, having authored 31 papers that have together received 1.6k indexed citations. Recurring topics across this work include Animal testing and alternatives (8 papers), Toxic Organic Pollutants Impact (7 papers), Effects and risks of endocrine disrupting chemicals (6 papers), Carcinogens and Genotoxicity Assessment (4 papers), Bioinformatics and Genomic Networks (4 papers), Gene expression and cancer classification (4 papers), Environmental Toxicology and Ecotoxicology (3 papers) and Gene Regulatory Network Analysis (3 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (758 citations), Developmental Neuroscience (86 citations), Small Animals (229 citations), Cancer Research (158 citations) and Computational Theory and Mathematics (96 citations). Fred Parham has collaborated with scholars based in United States, Canada and Netherlands. Frequent co-authors include Christopher Jude Portier, Scott A. Masten, Larry L. Needham, Mamta Behl, Kristen Ryan, Raymond R. Tice, Michael D. Shelby, Oksana Sirenko, Jui‐Hua Hsieh and Hazel B. Matthews. Their work appears in journals such as Environmental Health Perspectives, Toxicological Sciences, Toxicology and Applied Pharmacology, Environmental Research and Bioinformatics.

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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