Claire N. Bedbrook

1.8k citations
19 papers · 1.1k indexed · 1 hit paper · h-index 15
Topics
Photoreceptor and optogenetics research (7 papers)Molecular Communication and Nanonetworks (4 papers)Fish biology, ecology, and behavior (4 papers)
Partner nations
United StatesRussia

In The Last Decade

Claire N. Bedbrook

18 papers receiving 1.1k citations

Hit Papers

Learned protein embeddings for machine learning2018202620202023201850100150200

Peers

Claire N. Bedbrook
Comparison fields: 5 of 105
  • Molecular Biology 631
  • Cellular and Molecular Neuroscience 330
  • Biomedical Engineering 208
  • Cognitive Neuroscience 177
  • Genetics 102
Replace Kiwamu Takemoto with:
Kiwamu Takemoto Japan
Lea Goentoro United States
Shiqiang Gao Germany
John M. Mendenhall United States
Shohei Maékawa Japan
Haruki Takeuchi Japan
Tyler Cutforth United States
Naomi Kamasawa United States
Yukako Asai Japan
Caroline C. Overly United States
Claire N. Bedbrook relative to Kiwamu Takemoto Japan Kiwamu Takemoto's profile →
Citations per field
00.5×1.5×2.4×
Kiwamu Takemoto · 1×
Citations per year

Countries citing papers authored by Claire N. Bedbrook

Since Specialization
Citations

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

Fields of papers citing papers by Claire N. Bedbrook

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Claire N. Bedbrook. 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 Claire N. Bedbrook. The network helps show where Claire N. Bedbrook may publish in the future.

Co-authorship network of co-authors of Claire N. Bedbrook

This figure shows the co-authorship network connecting the top 25 collaborators of Claire N. Bedbrook. A scholar is included among the top collaborators of Claire N. Bedbrook based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Claire N. Bedbrook. Claire N. Bedbrook is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
#WorkIndexed citations
1 0
2 15
3 2
4 7
5 23
6 136
7 126
8
Learned protein embeddings for machine learningbreakdown →
202
9 82
10 151
11 51
12 46
13 41
14 51
15 107
16 1
17 14
18 48
19 38

About Claire N. Bedbrook

Claire N. Bedbrook is a scholar working on Aquatic Science, Cellular and Molecular Neuroscience and Nature and Landscape Conservation, having authored 19 papers that have together received 1.1k indexed citations. Recurring topics across this work include Photoreceptor and optogenetics research (7 papers), Molecular Communication and Nanonetworks (4 papers) and Fish biology, ecology, and behavior (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (330 citations), Aging (25 citations) and Endocrine and Autonomic Systems (92 citations). Claire N. Bedbrook has collaborated with scholars based in United States and Russia. Frequent co-authors include Frances H. Arnold, Viviana Gradinaru, Kevin Yang, Zachary Wu, Benjamin E. Deverman, Paul W. Sternberg, Clayton J. Radke, Austin J. Rice, Ravi D. Nath and Elisha D.W. Mackey. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

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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2026