Emma Byrne

876 citations
9 papers · 523 indexed · h-index 5
Topics
Semantic Web and Ontologies (4 papers)Microbial Metabolic Engineering and Bioproduction (3 papers)Neural Networks and Applications (2 papers)
Partner nations
United KingdomMalta

In The Last Decade

Emma Byrne

9 papers receiving 493 citations

Peers

Emma Byrne
Comparison fields: 5 of 116
  • Molecular Biology 187
  • Artificial Intelligence 125
  • Biomedical Engineering 86
  • Materials Chemistry 83
  • Computational Theory and Mathematics 64
Replace Michael J. Young with:
Michael J. Young United Kingdom
Wayne Aubrey United Kingdom
Kenneth E. Whelan United Kingdom
Philip G. K. Reiser New Zealand
Christopher H. Bryant United Kingdom
Ffion Mair Jones United Kingdom
Rafael C. Jiménez United Kingdom
Michael B. O’Connor United Kingdom
Carlo Torniai United States
Michael Krone Germany
Emma Byrne relative to Michael J. Young United Kingdom Michael J. Young's profile →
Citations per field
00.5×1.5×
Michael J. Young · 1×
Citations per year

Countries citing papers authored by Emma Byrne

Since Specialization
Citations

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

Fields of papers citing papers by Emma Byrne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emma Byrne

This figure shows the co-authorship network connecting the top 25 collaborators of Emma Byrne. A scholar is included among the top collaborators of Emma Byrne 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 Emma Byrne. Emma Byrne is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
#WorkIndexed citations
1
CABot3: A Simulated Neural Games Agent.
2
2 101
3 9
4 390
5 4
6 4
7
A Logical Framework for Identifying and Explaining Unexpected News.
1
8 3
9 9

About Emma Byrne

Emma Byrne is a scholar working on Artificial Intelligence, Information Systems and Management and Computational Theory and Mathematics, having authored 9 papers that have together received 523 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (4 papers), Microbial Metabolic Engineering and Bioproduction (3 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Information Systems and Management (62 citations), Biophysics (26 citations) and Computational Theory and Mathematics (64 citations). Emma Byrne has collaborated with scholars based in United Kingdom and Malta. Frequent co-authors include Maria Liakata, Amanda Clare, Wayne Aubrey, Ross D. King, Jem J. Rowland, Michael J. Young, Andrew C. Sparkes, Kenneth E. Whelan, Larisa Soldatova and Stephen G. Oliver. Their work appears in journals such as Science, Neurocomputing and Data & Knowledge Engineering.

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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