David Higgins

1.7k citations
20 papers · 946 · h-index 14

Impact in

  • Genetics top 10%
    • Genetic Mapping and Diversity in Plants and Animals
    • Genetic Associations and Epidemiology
    • Genetic and phenotypic traits in livestock

Papers in

    • Genetic Mapping and Diversity in Plants and Animals 6
    • Genetic and phenotypic traits in livestock 4

David Higgins

19 papers receiving 929 citations

Peers

David Higgins
Comparison fields: 5 of 111
  • Health Informatics 48
  • Genetics 306
  • Complementary and alternative medicine 89
  • Orthopedics and Sports Medicine 85
  • Immunology 176
Replace Ying Cui with:
Ying Cui China
S. Leichtweis United States
Jian‐Feng Tu China
Sayonara Rangel Oliveira Brazil
Katja E. Odening Germany
David Amar Israel
Xinxin Liao China
Hyun‐Seok Jin South Korea
Xiantao Tai China
Ola Hansson Sweden
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Citations per field
00.5×10×14.2×
Ying Cui · 1×
Citations per year

Countries citing papers authored by David Higgins

Since Specialization
Citations

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

Fields of papers citing papers by David Higgins

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 2005224
2 2001176
3 2007120
4 200487
5 202064
6 201641
7 202239
8 200234
9 200431
10 199827
11 200123
12 201422
13 201419
14 201515
15 202311
16 19976
17 20095
18 20241
19 20231
20 20230

About David Higgins

David Higgins is a scholar working on Molecular Biology, Genetics, Cellular and Molecular Neuroscience, Immunology and Health Information Management, having authored 20 papers that have together received 946 indexed citations. Recurring topics across this work include Genetic Mapping and Diversity in Plants and Animals (6 papers), Genetic and phenotypic traits in livestock (4 papers), Atherosclerosis and Cardiovascular Diseases (3 papers), Neuroscience and Neuropharmacology Research (3 papers), Artificial Intelligence in Healthcare and Education (2 papers), Pregnancy and preeclampsia studies (2 papers), Adipose Tissue and Metabolism (2 papers) and Cancer Genomics and Diagnostics (2 papers). The work is most often cited by research in Health Informatics (48 citations), Genetics (306 citations), Complementary and alternative medicine (89 citations), Orthopedics and Sports Medicine (85 citations) and Immunology (176 citations). David Higgins has collaborated with scholars based in United States, Germany and Ireland. Frequent co-authors include Beverly Paigen, Vince I. Madai, Xiao‐Song Wang, Haralambos Gavras, Fumihiro Sugiyama, Conrado Johns, Gary A. Churchill, Ron Korstanje, Jochen Einbeck and Peter M. Kelmenson. Their work appears in journals such as Mammalian Genome, Nature Genetics, Cell Reports, Therapeutic Innovation & Regulatory Science and American Journal of Obstetrics and Gynecology.

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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