David C. Wight

1.6k citations
23 papers · 1.3k · h-index 16

Impact in

Papers in

    • CRISPR and Genetic Engineering 4
    • Plant and Fungal Species Descriptions 3
    • Animal Genetics and Reproduction 9
    • Virus-based gene therapy research 5

David C. Wight

23 papers receiving 1.2k citations

Peers

David C. Wight
Comparison fields: 5 of 117
  • Endocrinology, Diabetes and Metabolism 321
  • Cardiology and Cardiovascular Medicine 305
  • Molecular Biology 625
  • Paleontology 68
  • Ecology, Evolution, Behavior and Systematics 180
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Citations per field
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Citations per year

Countries citing papers authored by David C. Wight

Since Specialization
Citations

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

Fields of papers citing papers by David C. Wight

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David C. Wight. 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 David C. Wight. The network helps show where David C. Wight may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996218
2 1990151
3 1991135
4 1997133
5 1995116
6 199473
7 198465
8 199157
9 198950
10 198241
11 199537
12 198928
13 199425
14 198323
15 198722
16 200320
17 198415
18 197613
19 199012
20 199610

About David C. Wight

David C. Wight is a scholar working on Molecular Biology, Genetics, Ecology, Evolution, Behavior and Systematics, Paleontology and Endocrinology, Diabetes and Metabolism, having authored 23 papers that have together received 1.3k indexed citations. Recurring topics across this work include Animal Genetics and Reproduction (9 papers), Plant Diversity and Evolution (6 papers), Virus-based gene therapy research (5 papers), CRISPR and Genetic Engineering (4 papers), Plant and Fungal Species Descriptions (3 papers), Paleontology and Stratigraphy of Fossils (3 papers), Growth Hormone and Insulin-like Growth Factors (3 papers) and Cardiac electrophysiology and arrhythmias (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (321 citations), Cardiology and Cardiovascular Medicine (305 citations), Molecular Biology (625 citations), Paleontology (68 citations) and Ecology, Evolution, Behavior and Systematics (180 citations). David C. Wight has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Thomas E. Wagner, John J. Kopchick, Charles B. Beck, Yoshihiro Ishikawa, Dorothy E. Vatner, C J Homcy, William E. Stein, Richard P. Shannon, Mitsunori Iwase and Raymond K. Kudej. Their work appears in journals such as Review of Palaeobotany and Palynology, Journal of Neuroscience, Transgenic Research, Molecular Endocrinology and Experimental Biology and Medicine.

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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