David Moi

816 citations
10 papers · 264 · h-index 9

Impact in

    • Genomics and Phylogenetic Studies
    • RNA and protein synthesis mechanisms
    • Machine Learning in Bioinformatics
    • Bioinformatics and Genomic Networks
    • RNA modifications and cancer
    • Gene expression and cancer classification

Papers in

    • Genomics and Phylogenetic Studies 6
    • Machine Learning in Bioinformatics 4
    • RNA and protein synthesis mechanisms 3
    • Signaling Pathways in Disease 1
    • Insect and Arachnid Ecology and Behavior 2

David Moi

10 papers receiving 263 citations

Peers

David Moi
Comparison fields: 5 of 70
  • Aging 5
  • Molecular Biology 179
  • Genetics 63
  • Cellular and Molecular Neuroscience 26
  • Sensory Systems 6
Replace Yangyun Zou with:
Yangyun Zou China
Manyuan Long United States
Yannis Nevers Switzerland
Bruno M.C. Martins United Kingdom
William J. Rowell United States
Brian D. Aevermann United States
Nga Thi Thuy Nguyen France
Sibylle C. Vonesch Switzerland
Núria Casas-Vila Germany
Scott Cain United States
David Moi relative to Yangyun Zou China Yangyun Zou's profile →
Citations per field
00.5×8.6×
Yangyun Zou · 1×
Citations per year

Countries citing papers authored by David Moi

Since Specialization
Citations

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

Fields of papers citing papers by David Moi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

10 of 10 papers shown
#Work
1 2020119
2 202337
3 202224
4 202121
5 202016
6 202014
7 202310
8 20219
9 20258
10 20256

About David Moi

David Moi is a scholar working on Molecular Biology, Genetics, Cellular and Molecular Neuroscience, Ecology, Evolution, Behavior and Systematics and Ecology, having authored 10 papers that have together received 264 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (6 papers), Machine Learning in Bioinformatics (4 papers), RNA and protein synthesis mechanisms (3 papers), Insect and Arachnid Ecology and Behavior (2 papers), Neurobiology and Insect Physiology Research (2 papers), Signaling Pathways in Disease (1 paper), Plant and animal studies (1 paper) and Insect Utilization and Effects (1 paper). The work is most often cited by research in Aging (5 citations), Molecular Biology (179 citations), Genetics (63 citations), Cellular and Molecular Neuroscience (26 citations) and Sensory Systems (6 citations). David Moi has collaborated with scholars based in Switzerland, United Kingdom and Uruguay. Frequent co-authors include Christophe Dessimoz, Natasha Glover, Yannis Nevers, Adrian Altenhoff, Alex Warwick Vesztrocy, Tarcisio Mendes de Farias, Kimberly J. Gilbert, Victor Rossier, Richard Benton and Pablo S. Aguilar. Their work appears in journals such as Nucleic Acids Research, Nature Methods, PLoS Computational Biology, Molecular Biology and Evolution and Current 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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