Ross D. King

10.7k citations
155 papers · 5.8k · h-index 39

Impact in

Papers in

    • Microbial Metabolic Engineering and Bioproduction 21
    • Machine Learning in Bioinformatics 20
    • Biomedical Text Mining and Ontologies 17
    • Protein Structure and Dynamics 15
    • Bioinformatics and Genomic Networks 11
    • Computational Drug Discovery Methods 40

Ross D. King

149 papers receiving 5.5k citations

Peers

Ross D. King
Comparison fields: 5 of 197
  • Computational Theory and Mathematics 1.1k
  • Artificial Intelligence 1.4k
  • Molecular Biology 2.7k
  • Information Systems and Management 189
  • Information Systems 589
Replace Limsoon Wong with:
Limsoon Wong Singapore
Michael Schroeder Germany
Stephen Muggleton United Kingdom
Dong Xu United States
Doheon Lee South Korea
Michael R. Berthold Germany
Matthias Dehmer Austria
Blaž Zupan Slovenia
Vasant Honavar United States
David K. Gifford United States
Ross D. King relative to Limsoon Wong Singapore Limsoon Wong's profile →
Citations per field
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Citations per year

Countries citing papers authored by Ross D. King

Since Specialization
Citations

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

Fields of papers citing papers by Ross D. King

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ross D. King. 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 Ross D. King. The network helps show where Ross D. King may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 155 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009401
2 2004395
3 1996368
4 2005290
5 2000283
6 1995208
7 2002182
8 1992140
9 1992138
10 2001132
11 1996130
12 1996128
13 2006122
14
Finding frequent substructures in chemical compounds
1998119
15 2010105
16 2003103
17 201599
18 201996
19 201082
20 199080

About Ross D. King

Ross D. King is a scholar working on Molecular Biology, Computational Theory and Mathematics, Artificial Intelligence, Spectroscopy and Materials Chemistry, having authored 155 papers that have together received 5.8k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (40 papers), Microbial Metabolic Engineering and Bioproduction (21 papers), Machine Learning in Bioinformatics (20 papers), Biomedical Text Mining and Ontologies (17 papers), Protein Structure and Dynamics (15 papers), Analytical Chemistry and Chromatography (12 papers), Semantic Web and Ontologies (11 papers) and Bioinformatics and Genomic Networks (11 papers). The work is most often cited by research in Computational Theory and Mathematics (1.1k citations), Artificial Intelligence (1.4k citations), Molecular Biology (2.7k citations), Information Systems and Management (189 citations) and Information Systems (589 citations). Ross D. King has collaborated with scholars based in United Kingdom, Sweden and United States. Frequent co-authors include Michael J.E. Sternberg, Stephen Muggleton, Larisa Soldatova, Ashwin Srinivasan, Amanda Clare, Mohammed Ouali, Douglas B. Kell, Stephen G. Oliver, Kenneth E. Whelan and Janet A. Taylor. Their work appears in journals such as Bioinformatics, Proceedings of the National Academy of Sciences, Journal of The Royal Society Interface, Machine Learning and Protein Engineering Design and Selection.

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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