Emily Dolson

683 citations
32 papers · 106 · h-index 6

Impact in

Papers in

    • Evolution and Genetic Dynamics 15
    • Genetic diversity and population structure 2
    • Genomics and Phylogenetic Studies 4
    • Gene Regulatory Network Analysis 3

Emily Dolson

26 papers receiving 102 citations

Peers

Emily Dolson
Comparison fields: 5 of 41
  • General Dentistry 3
  • Artificial Intelligence 47
  • Genetics 30
  • Computer Science Applications 4
  • Molecular Biology 48
Replace Tejas Shah with:
Tejas Shah United Kingdom
Nicolás López Carranza United Kingdom
Ron Hübler Germany
Matteo Gnocchi Italy
Moritz Herrmann Germany
Vincent Rubinetti United States
Javier Mendoza‐Revilla United Kingdom
Oindrila Saha United States
Christian Stocker Switzerland
Siguo Wang China
Emily Dolson relative to Tejas Shah United Kingdom Tejas Shah's profile →
Citations per field
00.5×6.5×
Tejas Shah · 1×
Citations per year

Countries citing papers authored by Emily Dolson

Since Specialization
Citations

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

Fields of papers citing papers by Emily Dolson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Emily Dolson, 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 Emily Dolson Line = papers co-authored together Emily Dolson 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 201923
2 202016
3 20239
4 20228
5 20197
6 20216
7 20205
8 20224
9 20183
10 20163
11 20183
12 20242
13 20182
14 20222
15 20172
16 20231
17 20241
18 20241
19 20231
20 20231

About Emily Dolson

Emily Dolson is a scholar working on Genetics, Molecular Biology, Artificial Intelligence, Sociology and Political Science and Ecology, Evolution, Behavior and Systematics, having authored 32 papers that have together received 106 indexed citations. Recurring topics across this work include Evolution and Genetic Dynamics (15 papers), Evolutionary Algorithms and Applications (10 papers), Evolutionary Game Theory and Cooperation (7 papers), Genomics and Phylogenetic Studies (4 papers), Metaheuristic Optimization Algorithms Research (4 papers), Gene Regulatory Network Analysis (3 papers), Genetic diversity and population structure (2 papers) and Animal Behavior and Reproduction (2 papers). The work is most often cited by research in General Dentistry (3 citations), Artificial Intelligence (47 citations), Genetics (30 citations), Computer Science Applications (4 citations) and Molecular Biology (48 citations). Emily Dolson has collaborated with scholars based in United States, United Kingdom and Norway. Frequent co-authors include Charles Ofria, Alexander Lalejini, Luis Zaman, Michael J. Wiser, David Baum, Eric Smith, Davis T. Weaver, Masahiro Hitomi, Curtis J. Donskey and Jacob G. Scott. Their work appears in journals such as Artificial Life, Frontiers in Ecology and Evolution, Science Advances, Journal of The Royal Society Interface and eLife.

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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