Don Gilbert

4.4k citations
24 papers · 587 · h-index 11

Impact in

Papers in

    • Genetics, Bioinformatics, and Biomedical Research 8
    • Genomics and Phylogenetic Studies 7
    • Molecular Biology Techniques and Applications 3
    • Bioinformatics and Genomic Networks 3
    • Gene expression and cancer classification 3
    • Machine Learning in Bioinformatics 2
    • Scientific Computing and Data Management 3

Don Gilbert

24 papers receiving 576 citations

Peers

Don Gilbert
Comparison fields: 5 of 92
  • Aging 10
  • Ecology 128
  • Genetics 137
  • Insect Science 58
  • Ecology, Evolution, Behavior and Systematics 91
Replace Shin‐ichi Tokishita with:
Shin‐ichi Tokishita Japan
Richard Smith-Unna United Kingdom
György Abrusán Germany
Loı̈c Ponger France
Arto Soitamo Finland
Bruce J. Cochrane United States
Gabino Sanchez‐Perez Netherlands
Ying Shen China
Tamar Lotan Israel
Elena Drosopoulou Greece
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Citations per field
00.5×2.5×
Shin‐ichi Tokishita · 1×
Citations per year

Countries citing papers authored by Don Gilbert

Since Specialization
Citations

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

Fields of papers citing papers by Don Gilbert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005113
2 198575
3 200565
4 201053
5 201651
6 200441
7 201737
8 200234
9 200332
10 201927
11 200816
12 200410
13 19907
14 20166
15 20034
16 20094
17 20033
18 20022
19 20162
20 20021

About Don Gilbert

Don Gilbert is a scholar working on Molecular Biology, Information Systems and Management, Nature and Landscape Conservation, Genetics and Plant Science, having authored 24 papers that have together received 587 indexed citations. Recurring topics across this work include Genetics, Bioinformatics, and Biomedical Research (8 papers), Genomics and Phylogenetic Studies (7 papers), Scientific Computing and Data Management (3 papers), Molecular Biology Techniques and Applications (3 papers), Bioinformatics and Genomic Networks (3 papers), Gene expression and cancer classification (3 papers), Machine Learning in Bioinformatics (2 papers) and Chromosomal and Genetic Variations (2 papers). The work is most often cited by research in Aging (10 citations), Ecology (128 citations), Genetics (137 citations), Insect Science (58 citations) and Ecology, Evolution, Behavior and Systematics (91 citations). Don Gilbert has collaborated with scholars based in United States, Australia and South Korea. Frequent co-authors include John K. Colbourne, Vasanth Singan, William T. Starmer, Ralph Tollrian, Michael E. Pfrender, Florian Leese, Katina I. Spanier, Christoph Mayer, Haixu Tang and Sun Kim. Their work appears in journals such as Briefings in Bioinformatics, Bioinformatics, Computer applications in the biosciences, PeerJ and BMC Molecular Biology.

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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