Ted Slater

18.3k citations
5 papers · 205 · h-index 5

Impact in

Papers in

    • Biomedical Text Mining and Ontologies 2
    • Bioinformatics and Genomic Networks 2
    • Genomics and Phylogenetic Studies 1
    • Gene Regulatory Network Analysis 1
    • Microbial Metabolic Engineering and Bioproduction 1
    • Semantic Web and Ontologies 2

Ted Slater

5 papers receiving 199 citations

Peers

Ted Slater
Comparison fields: 5 of 51
  • Cell Biology 43
  • Information Systems and Management 17
  • Molecular Biology 138
  • Plant Science 65
  • Computational Theory and Mathematics 21
Replace Esmeralda Vicedo with:
Esmeralda Vicedo Germany
Yannis Nevers Switzerland
Hanna Ćwiek‐Kupczyńska Poland
Mary Ann Tuli United Kingdom
Matthieu Reichstadt France
Laëtitia Guillot France
Guenter Stoesser United Kingdom
Scheila de Ávila e Silva Brazil
Olivier Andrieu France
Will DeLoache United States
Ted Slater relative to Esmeralda Vicedo Germany Esmeralda Vicedo's profile →
Citations per field
00.5×2×3×4.3×
Esmeralda Vicedo · 1×
Citations per year

Countries citing papers authored by Ted Slater

Since Specialization
Citations

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

Fields of papers citing papers by Ted Slater

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

About Ted Slater

Ted Slater is a scholar working on Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics, Public Health, Environmental and Occupational Health and Cell Biology, having authored 5 papers that have together received 205 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (2 papers), Bioinformatics and Genomic Networks (2 papers), Semantic Web and Ontologies (2 papers), Genomics and Phylogenetic Studies (1 paper), Computational Drug Discovery Methods (1 paper), Gene Regulatory Network Analysis (1 paper), Microbial Metabolic Engineering and Bioproduction (1 paper) and Plant Pathogens and Fungal Diseases (1 paper). The work is most often cited by research in Cell Biology (43 citations), Information Systems and Management (17 citations), Molecular Biology (138 citations), Plant Science (65 citations) and Computational Theory and Mathematics (21 citations). Ted Slater has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Enoch S. Huang, Christopher M. L. S. Bouton, Bradley C. Hyman, Matthew M. Tanzer, Todd M. DeZwaan, Blaise A. Darveaux, John E. Hamer, Kiichi Adachi, Ryan W. Heiniger and Clive Lo. Their work appears in journals such as Drug Discovery Today, Proceedings of the National Academy of Sciences and Genetics.

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.

Explore authors with similar magnitude of impact