Fred Parham

1.9k citations
32 papers · 1.2k · h-index 19

Impact in

Papers in

Fred Parham

30 papers receiving 1.2k citations

Peers

Fred Parham
Comparison fields: 5 of 117
  • Health, Toxicology and Mutagenesis 556
  • Small Animals 136
  • Developmental Neuroscience 76
  • Pollution 151
  • Cancer Research 135
Replace Jui‐Hua Hsieh with:
Jui‐Hua Hsieh United States
Fabian A. Grimm United States
Shirlee Tan United States
Tomasz Sobański Poland
Andrea Terron Italy
Martin Paparella Italy
Derik E. Haggard United States
Ram Ramabhadran United States
Jorge M. Naciff United States
Ila Cote United States
Fred Parham relative to Jui‐Hua Hsieh United States Jui‐Hua Hsieh's profile →
Citations per field
00.5×1.5×1.8×
Jui‐Hua Hsieh · 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 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019206
2 2018153
3 2016101
4 200887
5 199779
6 200270
7 201766
8 201861
9 201840
10 200936
11 200435
12 199634
13 201823
14 200422
15 201620
16 199820
17 201219
18 200419
19 200618
20 200916

About Fred Parham

Fred Parham is a scholar working on Molecular Biology, Health, Toxicology and Mutagenesis, Small Animals, Computational Theory and Mathematics and Cancer Research, having authored 32 papers that have together received 1.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Animal testing and alternatives (9 papers), Effects and risks of endocrine disrupting chemicals (8 papers), Carcinogens and Genotoxicity Assessment (6 papers), Pharmacogenetics and Drug Metabolism (4 papers), Pluripotent Stem Cells Research (4 papers), Gene expression and cancer classification (4 papers) and Gene Regulatory Network Analysis (4 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (556 citations), Small Animals (136 citations), Developmental Neuroscience (76 citations), Pollution (151 citations) and Cancer Research (135 citations). Fred Parham has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Christopher J. Portier, Mamta Behl, Kristen Ryan, Raymond R. Tice, Scott A. Masten, Oksana Sirenko, H.B. Matthews, Jui‐Hua Hsieh, Daniel Svoboda and Scott S. Auerbach. Their work appears in journals such as Environmental Health Perspectives, Toxicological Sciences, Toxicology and Applied Pharmacology, Bioinformatics and Environmental Research.

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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