Gavin Harper

1.6k total citations · 1 hit paper
16 papers, 1.1k citations indexed

About

Gavin Harper is a scholar working on Computational Theory and Mathematics, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Gavin Harper has authored 16 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computational Theory and Mathematics, 7 papers in Molecular Biology and 4 papers in Artificial Intelligence. Recurrent topics in Gavin Harper's work include Computational Drug Discovery Methods (10 papers), Bioinformatics and Genomic Networks (3 papers) and Analytical Chemistry and Chromatography (2 papers). Gavin Harper is often cited by papers focused on Computational Drug Discovery Methods (10 papers), Bioinformatics and Genomic Networks (3 papers) and Analytical Chemistry and Chromatography (2 papers). Gavin Harper collaborates with scholars based in United Kingdom, Finland and India. Gavin Harper's co-authors include Andrew R. Leach, Michael M. Hann, Stephen D. Pickett, Darren V. S. Green, Gary K. Smith, Klaus Schneider, David H. Drewry, Paul Bamborough, Steward T. A. Pickett and John Gittins and has published in prestigious journals such as Journal of Medicinal Chemistry, Drug Discovery Today and Journal of Chemical Information and Modeling.

In The Last Decade

Gavin Harper

15 papers receiving 1.1k citations

Hit Papers

Molecular Complexity and Its Impact on the Probability of... 2001 2026 2009 2017 2001 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Molecular Complexity and Its Impact on the Probability of Finding Leads for Drug Discovery
    2001 613 citations Michael M. Hann, Andrew R. Leach et al. Journal of Chemical Information and Computer Sciences profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Gavin Harper United Kingdom 11 745 725 216 174 126 16 1.1k
Xiao Qing Lewell United Kingdom 12 717 1.0× 727 1.0× 214 1.0× 216 1.2× 154 1.2× 18 1.1k
Brian Clarke United Kingdom 3 933 1.3× 862 1.2× 264 1.2× 160 0.9× 211 1.7× 7 1.4k
Iain M. McLay United Kingdom 22 695 0.9× 658 0.9× 402 1.9× 233 1.3× 133 1.1× 32 1.5k
Pierre Acklin Switzerland 19 844 1.1× 963 1.3× 263 1.2× 183 1.1× 220 1.7× 28 1.6k
Giovanna Tedesco Italy 12 1.1k 1.4× 891 1.2× 386 1.8× 171 1.0× 218 1.7× 15 1.6k
Andrew Smellie United States 11 740 1.0× 616 0.8× 234 1.1× 122 0.7× 73 0.6× 19 1.1k
Markus Wagener Germany 17 716 1.0× 869 1.2× 226 1.0× 100 0.6× 182 1.4× 30 1.3k
Christian Lemmen Germany 16 806 1.1× 904 1.2× 182 0.8× 180 1.0× 247 2.0× 32 1.3k
Tanja Schulz‐Gasch Switzerland 17 1.2k 1.7× 703 1.0× 268 1.2× 250 1.4× 237 1.9× 27 1.7k
Weifan Zheng United States 19 685 0.9× 786 1.1× 241 1.1× 132 0.8× 186 1.5× 44 1.3k

Countries citing papers authored by Gavin Harper

Since Specialization
Citations

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

Fields of papers citing papers by Gavin Harper

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gavin Harper

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

All Works

16 of 16 papers shown
1.
Keskinarkaus, Anja, et al.. (2017). Architecture Enabling Service-oriented Digital Biobanks. Proceedings of the ... Annual Hawaii International Conference on System Sciences. 3 indexed citations
2.
Harper, Gavin, et al.. (2017). Defining an architecture for evolving environments. University of Oulu Repository (University of Oulu). 1178–1181.
3.
Harper, Gavin. (2011). Viability of artificial neural networks in mobile healthcare. Theseus (Ammattikorkeakoulujen). 1 indexed citations
4.
Clark, Liz, Emilio Dı́ez, Gavin Harper, et al.. (2009). Process Validation and Screen Reproducibility in High-Throughput Screening. SLAS DISCOVERY. 14(1). 66–76. 27 indexed citations
5.
Birchall, Kristian, Valerie J. Gillet, Gavin Harper, & Stephen D. Pickett. (2008). Evolving Interpretable Structure−Activity Relationship Models. 2. Using Multiobjective Optimization To Derive Multiple Models. Journal of Chemical Information and Modeling. 48(8). 1558–1570. 18 indexed citations
6.
Bamborough, Paul, David H. Drewry, Gavin Harper, Gary K. Smith, & Klaus Schneider. (2008). Assessment of Chemical Coverage of Kinome Space and Its Implications for Kinase Drug Discovery. Journal of Medicinal Chemistry. 51(24). 7898–7914. 126 indexed citations
7.
Birchall, Kristian, Valerie J. Gillet, Gavin Harper, & Stephen D. Pickett. (2008). Evolving Interpretable Structure−Activity Relationships. 1. Reduced Graph Queries. Journal of Chemical Information and Modeling. 48(8). 1543–1557. 14 indexed citations
8.
Harper, Gavin & Stephen D. Pickett. (2006). Methods for mining HTS data. Drug Discovery Today. 11(15-16). 694–699. 35 indexed citations
9.
Birchall, Kristian, Valerie J. Gillet, Gavin Harper, & Stephen D. Pickett. (2006). Training Similarity Measures for Specific Activities:  Application to Reduced Graphs. Journal of Chemical Information and Modeling. 46(2). 577–586. 25 indexed citations
10.
Harper, Gavin. (2006). Solar Energy Projects for the Evil Genius. Medical Entomology and Zoology. 5 indexed citations
11.
Harper, Gavin, Steward T. A. Pickett, & Darren V. S. Green. (2004). (Research Papers) Design of a Compound Screening Collection for use in High Throughput Screening. Combinatorial Chemistry & High Throughput Screening. 7(1). 63–70. 49 indexed citations
12.
Harper, Gavin, et al.. (2004). The Reduced Graph Descriptor in Virtual Screening and Data-Driven Clustering of High-Throughput Screening Data. Journal of Chemical Information and Computer Sciences. 44(6). 2145–2156. 62 indexed citations
13.
Lewell, Xiao Qing, et al.. (2003). Drug Rings Database with Web Interface. A Tool for Identifying Alternative Chemical Rings in Lead Discovery Programs. Journal of Medicinal Chemistry. 46(15). 3257–3274. 61 indexed citations
14.
Hann, Michael M., Andrew R. Leach, & Gavin Harper. (2001). Molecular Complexity and Its Impact on the Probability of Finding Leads for Drug Discovery. Journal of Chemical Information and Computer Sciences. 41(3). 856–864. 613 indexed citations breakdown →
15.
Harper, Gavin, John Bradshaw, John Gittins, Darren V. S. Green, & Andrew R. Leach. (2001). Prediction of Biological Activity for High-Throughput Screening Using Binary Kernel Discrimination. Journal of Chemical Information and Computer Sciences. 41(5). 1295–1300. 71 indexed citations
16.
Harper, Gavin. (1968). BOP---An approach to building optimization. 575–583. 6 indexed citations

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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