Peter G. Lord

1.7k total citations
36 papers, 1.1k citations indexed

About

Peter G. Lord is a scholar working on Molecular Biology, Pharmacology and Computational Theory and Mathematics. According to data from OpenAlex, Peter G. Lord has authored 36 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 7 papers in Pharmacology and 6 papers in Computational Theory and Mathematics. Recurrent topics in Peter G. Lord's work include Gene expression and cancer classification (8 papers), Computational Drug Discovery Methods (6 papers) and Pharmacogenetics and Drug Metabolism (5 papers). Peter G. Lord is often cited by papers focused on Gene expression and cancer classification (8 papers), Computational Drug Discovery Methods (6 papers) and Pharmacogenetics and Drug Metabolism (5 papers). Peter G. Lord collaborates with scholars based in United Kingdom, United States and Belgium. Peter G. Lord's co-authors include Alan E. Wheals, Syril Pettit, William D. Pennie, Michael McMillian, Alex Nie, Angelique M. Leone, J. Brandon Parker, T.C. Orton, Peter J. Bugelski and Lynn Yieh and has published in prestigious journals such as Biochemical and Biophysical Research Communications, Journal of Cell Science and Journal of Bacteriology.

In The Last Decade

Peter G. Lord

36 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter G. Lord United Kingdom 18 796 146 136 135 105 36 1.1k
François Pognan Switzerland 18 1.1k 1.3× 269 1.8× 207 1.5× 108 0.8× 179 1.7× 32 1.9k
Ni Ai China 20 621 0.8× 154 1.1× 129 0.9× 142 1.1× 70 0.7× 33 1.0k
Jeffrey A. Kramer United States 19 570 0.7× 136 0.9× 167 1.2× 85 0.6× 66 0.6× 38 1.1k
Richard D. Irwin United States 15 348 0.4× 118 0.8× 101 0.7× 214 1.6× 56 0.5× 33 880
Noriyuki Nakatsu Japan 15 660 0.8× 123 0.8× 227 1.7× 139 1.0× 99 0.9× 27 1.0k
Makoto Muroi Japan 25 1.2k 1.5× 84 0.6× 124 0.9× 175 1.3× 165 1.6× 78 1.8k
Robert Tonge United Kingdom 14 993 1.2× 82 0.6× 35 0.3× 88 0.7× 82 0.8× 18 1.5k
Dolores Diaz United States 15 618 0.8× 270 1.8× 203 1.5× 124 0.9× 259 2.5× 22 1.3k
Rong Chen China 19 849 1.1× 55 0.4× 113 0.8× 130 1.0× 38 0.4× 68 1.2k
Jiayi Yin China 20 768 1.0× 64 0.4× 289 2.1× 136 1.0× 107 1.0× 41 1.2k

Countries citing papers authored by Peter G. Lord

Since Specialization
Citations

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

Fields of papers citing papers by Peter G. Lord

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter G. Lord. 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 Peter G. Lord. The network helps show where Peter G. Lord may publish in the future.

Co-authorship network of co-authors of Peter G. Lord

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

All Works

20 of 20 papers shown
1.
Veeramachaneni, Vamsi, Xiang Yao, Alex Nie, et al.. (2015). Release of (and Lessons Learned from Mining) a Pioneering Large Toxicogenomics Database. Pharmacogenomics. 16(8). 779–801. 4 indexed citations
2.
Leone, Angelique M., Alex Nie, J. Brandon Parker, et al.. (2014). Oxidative stress/reactive metabolite gene expression signature in rat liver detects idiosyncratic hepatotoxicants. Toxicology and Applied Pharmacology. 275(3). 189–197. 37 indexed citations
3.
Fostel, Jennifer, Lyle D. Burgoon, Craig Zwickl, et al.. (2007). Toward a Checklist for Exchange and Interpretation of Data from a Toxicology Study. Toxicological Sciences. 99(1). 26–34. 13 indexed citations
4.
Lord, Peter G., Alex Nie, & Michael McMillian. (2006). The Evolution of Gene Expression Studies in Drug Safety Assessment. Toxicology Mechanisms and Methods. 16(2-3). 51–58. 2 indexed citations
5.
Leone, Anna, et al.. (2006). Hepatic expression of heme oxygenase-1 and antioxidant response element-mediated genes following administration of ethinyl estradiol to rats. Toxicology and Applied Pharmacology. 216(3). 416–425. 11 indexed citations
6.
Nie, Alex, Michael McMillian, J. Brandon Parker, et al.. (2006). Predictive toxicogenomics approaches reveal underlying molecular mechanisms of nongenotoxic carcinogenicity. Molecular Carcinogenesis. 45(12). 914–933. 123 indexed citations
7.
Lord, Peter G.. (2004). Progress in applying genomics in drug development. Toxicology Letters. 149(1-3). 371–375. 19 indexed citations
8.
Pennie, William D., Syril Pettit, & Peter G. Lord. (2004). Toxicogenomics in risk assessment: an overview of an HESI collaborative research program.. Environmental Health Perspectives. 112(4). 417–419. 84 indexed citations
9.
Crunkhorn, Sarah, et al.. (2003). Gene expression changes in rat liver following exposure to liver growth agents: role of Kupffer cells in xenobiotic-mediated liver growth. Biochemical Pharmacology. 67(1). 107–118. 17 indexed citations
10.
Bryant, Duncan, Peter J. Bugelski, Patrick Camilleri, et al.. (2003). Protein expression changes in the Sprague Dawley rat liver proteome following administration of peroxisome proliferator activated receptor α and γ ligands. PROTEOMICS. 3(4). 505–512. 20 indexed citations
11.
Plant, Nick, et al.. (2002). Differential Gene Expression in Rats Following Subacute Exposure to the Anticonvulsant Sodium Valproate. Toxicology and Applied Pharmacology. 183(2). 127–134. 13 indexed citations
12.
Lord, Peter G., et al.. (2002). Inter-individual variation in urothelial DNA repair gene expression in vitro. Toxicology in Vitro. 16(4). 383–387. 5 indexed citations
13.
Bryant, Duncan, Peter J. Bugelski, Patrick Camilleri, et al.. (2002). Protein expression analysis of drug-mediated hepatotoxicity in the Sprague-Dawley rat. PROTEOMICS. 2(11). 1577–1585. 26 indexed citations
14.
Bugelski, Peter J., et al.. (2000). A Strategy for Primary High Throughput Cytotoxicity Screening in Pharmaceutical Toxicology. Pharmaceutical Research. 17(10). 1265–1272. 20 indexed citations
15.
Fletcher, K. C., Peter G. Lord, Terry C. Orton, J.K. Chipman, & Alastair J. Strain. (1999). EGF-Induced Receptor Autophosphorylation in Primary Hepatocytes Isolated from Phenobarbitone-Treated Mice. Biochemical and Biophysical Research Communications. 260(2). 483–487. 2 indexed citations
16.
17.
Stanley, Lesley A., Dana Blackburn, Julie F. Foley, et al.. (1994). Ras mutations in methyiclofenapate-induced B6C3F1 and C57BL/1OJ mouse liver tumours. Carcinogenesis. 15(6). 1125–1131. 15 indexed citations
18.
Lord, Peter G., et al.. (1992). Point mutation analysis of ras genes in spontaneous and chemically induced C57Bl/10J mouse liver tumours. Carcinogenesis. 13(8). 1383–1387. 12 indexed citations
19.
Wheals, Alan E. & Peter G. Lord. (1992). Clonal heterogeneity in specific growth rate of Succhuromyces cerevisiue cells. Cell Proliferation. 25(3). 217–223. 14 indexed citations
20.
Routledge, Michael N., Terry C. Orton, Peter G. Lord, & R. Colin Garner. (1990). Effect of Butylated Hydroxyanisole on the Level of DNA Adduction by Aristolochic Acid in the Rat Forestomach and Liver. Japanese Journal of Cancer Research. 81(3). 220–224. 5 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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