K. Grime

663 total citations
12 papers, 419 citations indexed

About

K. Grime is a scholar working on Pharmacology, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, K. Grime has authored 12 papers receiving a total of 419 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Pharmacology, 5 papers in Computational Theory and Mathematics and 3 papers in Molecular Biology. Recurrent topics in K. Grime's work include Pharmacogenetics and Drug Metabolism (9 papers), Computational Drug Discovery Methods (5 papers) and Drug Transport and Resistance Mechanisms (3 papers). K. Grime is often cited by papers focused on Pharmacogenetics and Drug Metabolism (9 papers), Computational Drug Discovery Methods (5 papers) and Drug Transport and Resistance Mechanisms (3 papers). K. Grime collaborates with scholars based in United Kingdom, Sweden and Singapore. K. Grime's co-authors include Ronald T. Riley, Robert J. Riley, Dermot F. McGinnity, Patrick Barton, D. E. Briggs, Jane R. Kenny, Douglas Ferguson, Isabell Hultman, Annika Janefeldt and Britta Bonn and has published in prestigious journals such as Journal of Pharmaceutical Sciences, Drug Metabolism and Disposition and Molecular Pharmaceutics.

In The Last Decade

K. Grime

12 papers receiving 404 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
K. Grime United Kingdom 11 272 140 120 86 64 12 419
Weiqiao Chen United States 6 366 1.3× 117 0.8× 48 0.4× 121 1.4× 41 0.6× 8 560
Anna-Karin Sohlenius-Sternbeck Sweden 12 282 1.0× 212 1.5× 99 0.8× 171 2.0× 41 0.6× 22 594
Leslie M. Tompkins United States 6 316 1.2× 164 1.2× 58 0.5× 151 1.8× 22 0.3× 6 580
Stephanie D. Turner United States 7 439 1.6× 170 1.2× 118 1.0× 214 2.5× 80 1.3× 9 738
Shoko Ohmori Japan 10 445 1.6× 216 1.5× 63 0.5× 207 2.4× 53 0.8× 31 656
Y. Naritomi Japan 5 240 0.9× 147 1.1× 58 0.5× 74 0.9× 43 0.7× 11 389
Noriko Hirota Japan 3 413 1.5× 300 2.1× 91 0.8× 107 1.2× 65 1.0× 8 562
Quan Zhou China 13 189 0.7× 105 0.8× 41 0.3× 104 1.2× 51 0.8× 59 477
Kiran C. Patki United States 7 245 0.9× 137 1.0× 50 0.4× 58 0.7× 26 0.4× 13 435
Steven J. Pernecky United States 11 419 1.5× 196 1.4× 77 0.6× 228 2.7× 38 0.6× 18 645

Countries citing papers authored by K. Grime

Since Specialization
Citations

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

Fields of papers citing papers by K. Grime

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of K. Grime

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

All Works

12 of 12 papers shown
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Stresser, David M., et al.. (2013). Exploring concepts ofin vitrotime-dependent CYP inhibition assays. Expert Opinion on Drug Metabolism & Toxicology. 10(2). 157–174. 35 indexed citations
4.
Grime, K., Patrick Barton, & Dermot F. McGinnity. (2012). Application of In Silico, In Vitro and Preclinical Pharmacokinetic Data for the Effective and Efficient Prediction of Human Pharmacokinetics. Molecular Pharmaceutics. 10(4). 1191–1206. 53 indexed citations
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Grime, K., et al.. (2008). Mechanism-based inhibition of cytochrome P450 enzymes: An evaluation of early decision making in vitro approaches and drug–drug interaction prediction methods. European Journal of Pharmaceutical Sciences. 36(2-3). 175–191. 60 indexed citations
7.
Kenny, Jane R. & K. Grime. (2006). Pharmacokinetic consequences of time-dependent inhibition using the isolated perfused rat liver model. Xenobiotica. 36(5). 351–365. 12 indexed citations
8.
Grime, K. & Ronald T. Riley. (2006). The Impact of In Vitro Binding on In Vitro - In Vivo Extrapolations, Projections of Metabolic Clearance and Clinical Drug-Drug Interactions. Current Drug Metabolism. 7(3). 251–264. 91 indexed citations
9.
Soars, Matthew G., K. Grime, & Robert J. Riley. (2006). Comparative analysis of substrate and inhibitor interactions with CYP3A4 and CYP3A5. Xenobiotica. 36(4). 287–299. 33 indexed citations
10.
Grime, K., et al.. (2001). Rapid high-performance liquid chromatographic method for the separation of hydroxylated testosterone metabolites. Journal of Chromatography B Biomedical Sciences and Applications. 760(2). 281–288. 21 indexed citations
11.
Grime, K. & D. E. Briggs. (1996). THE RELEASE OF BOUND β-AMYLASE BY MACROMOLECULES. Journal of the Institute of Brewing. 102(4). 261–270. 20 indexed citations
12.
Grime, K. & D. E. Briggs. (1995). RELEASE AND ACTIVATION OF BARLEY β-AMYLASE. Journal of the Institute of Brewing. 101(5). 337–343. 11 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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