David W. Markby

750 total citations
15 papers, 477 citations indexed

About

David W. Markby is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Cell Biology. According to data from OpenAlex, David W. Markby has authored 15 papers receiving a total of 477 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 7 papers in Pulmonary and Respiratory Medicine and 5 papers in Cell Biology. Recurrent topics in David W. Markby's work include Renal cell carcinoma treatment (7 papers), Biochemical and Molecular Research (4 papers) and Hemoglobin structure and function (4 papers). David W. Markby is often cited by papers focused on Renal cell carcinoma treatment (7 papers), Biochemical and Molecular Research (4 papers) and Hemoglobin structure and function (4 papers). David W. Markby collaborates with scholars based in United States, France and United Kingdom. David W. Markby's co-authors include Henry R. Bourne, H. K. Schachman, René Onrust, Edward Eisenstein, James Newell, Andrew Flint, Ellen A. Robey, Susan R. Wente, Ying Yang and Philippe Merle and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

David W. Markby

15 papers receiving 471 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David W. Markby United States 10 288 112 102 98 91 15 477
Ruth Gutiérrez Spain 7 341 1.2× 32 0.3× 38 0.4× 101 1.0× 107 1.2× 11 715
Jessica J. Gierut United States 16 570 2.0× 69 0.6× 15 0.1× 285 2.9× 100 1.1× 23 767
Florence Polet Belgium 5 466 1.6× 31 0.3× 9 0.1× 75 0.8× 42 0.5× 6 662
Jun-Wei Liu United States 9 379 1.3× 25 0.2× 47 0.5× 107 1.1× 57 0.6× 12 573
Marianne Kelley United States 10 121 0.4× 45 0.4× 17 0.2× 72 0.7× 64 0.7× 17 380
Ilenia Agliarulo Italy 11 372 1.3× 104 0.9× 14 0.1× 75 0.8× 38 0.4× 12 476
Michael Bæk Denmark 6 414 1.4× 21 0.2× 9 0.1× 73 0.7× 37 0.4× 8 564
Frederick D. Tsai United States 7 466 1.6× 124 1.1× 25 0.2× 80 0.8× 12 0.1× 12 547
Nelma Pértega‐Gomes Portugal 14 482 1.7× 25 0.2× 6 0.1× 110 1.1× 212 2.3× 14 728
Alon Silberman Israel 8 338 1.2× 13 0.1× 11 0.1× 50 0.5× 43 0.5× 11 510

Countries citing papers authored by David W. Markby

Since Specialization
Citations

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

Fields of papers citing papers by David W. Markby

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David W. Markby. 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 David W. Markby. The network helps show where David W. Markby may publish in the future.

Co-authorship network of co-authors of David W. Markby

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

All Works

15 of 15 papers shown
1.
Kelley, Robin Kate, Tim Meyer, Lorenza Rimassa, et al.. (2020). Serum Alpha-fetoprotein Levels and Clinical Outcomes in the Phase III CELESTIAL Study of Cabozantinib versus Placebo in Patients with Advanced Hepatocellular Carcinoma. Clinical Cancer Research. 26(18). 4795–4804. 66 indexed citations
2.
Durán, Ignacio, Pablo Maroto, Cristina Suárez, et al.. (2019). Analysis of overall survival (OS) based on early tumor shrinkage in the phase III METEOR study of cabozantinib (cabo) versus everolimus (eve) in advanced renal cell carcinoma (RCC).. Journal of Clinical Oncology. 37(7_suppl). 550–550. 3 indexed citations
3.
Kelley, Robin Kate, Lorenza Rimassa, Baek‐Yeol Ryoo, et al.. (2019). Alpha fetoprotein (AFP) response and efficacy outcomes in the phase III CELESTIAL trial of cabozantinib (C) versus placebo (P) in advanced hepatocellular carcinoma (HCC).. Journal of Clinical Oncology. 37(4_suppl). 423–423. 7 indexed citations
4.
Powles, Thomas, Robert J. Motzer, Bernard Escudier, et al.. (2018). Outcomes based on prior therapy in the phase 3 METEOR trial of cabozantinib versus everolimus in advanced renal cell carcinoma. British Journal of Cancer. 119(6). 663–669. 66 indexed citations
5.
Kelley, Robin Kate, Anthony B. El-Khoueiry, Tim Meyer, et al.. (2018). Outcomes by baseline alpha-fetoprotein (AFP) levels in the phase III CELESTIAL trial of cabozantinib (C) versus placebo (P) in previously treated advanced hepatocellular carcinoma (HCC). Annals of Oncology. 29. viii236–viii236. 9 indexed citations
6.
Jonasch, Eric, Robert J. Motzer, Bernard Escudier, et al.. (2018). Cabozantinib (C) exposure-response (ER) modeling of efficacy and safety endpoints as a function of clearance in patients (pts) with renal cell carcinoma (RCC).. Journal of Clinical Oncology. 36(6_suppl). 645–645. 1 indexed citations
7.
Pal, Sumanta K., Robert J. Motzer, Mayer Fishman, et al.. (2017). Analysis of overall survival (OS) based on tumor target lesion change in the phase 3 METEOR trial of cabozantinib (cabo) versus everolimus (eve) in advanced renal cell carcinoma (RCC).. Journal of Clinical Oncology. 35(6_suppl). 522–522. 1 indexed citations
8.
Markby, David W., et al.. (1995). Solution Structure of the GTPase Activating Domain of αs. Journal of Molecular Biology. 254(4). 681–691. 14 indexed citations
9.
Benjamin, Dennis R., David W. Markby, Henry R. Bourne, & Irwin D. Kuntz. (1995). Complete 1H, 13C, and 15N Assignments and Secondary Structure of the GTPase Activating Domain of Gs. Biochemistry. 34(1). 155–162. 4 indexed citations
10.
Markby, David W., René Onrust, & Henry R. Bourne. (1993). Separate GTP Binding and GTPase Activating Domains of a Gα Subunit. Science. 262(5141). 1895–1901. 145 indexed citations
11.
Markby, David W., Bing Bing Zhou, & H. K. Schachman. (1991). A 70-amino acid zinc-binding polypeptide from the regulatory chain of aspartate transcarbamoylase forms a stable complex with the catalytic subunit leading to markedly altered enzyme activity.. Proceedings of the National Academy of Sciences. 88(23). 10568–10572. 12 indexed citations
12.
Eisenstein, Edward, David W. Markby, & H. K. Schachman. (1990). Heterotropic effectors promote a global conformational change in aspartate transcarbamoylase. Biochemistry. 29(15). 3724–3731. 43 indexed citations
13.
Eisenstein, Edward, David W. Markby, & H. K. Schachman. (1989). Changes in stability and allosteric properties of aspartate transcarbamoylase resulting from amino acid substitutions in the zinc-binding domain of the regulatory chains.. Proceedings of the National Academy of Sciences. 86(9). 3094–3098. 31 indexed citations
14.
Newell, James, David W. Markby, & H. K. Schachman. (1989). Cooperative binding of the bisubstrate analog N-(phosphonacetyl)-L-aspartate to aspartate transcarbamoylase and the heterotropic effects of ATP and CTP. Journal of Biological Chemistry. 264(5). 2476–2481. 41 indexed citations
15.
Robey, Ellen A., Susan R. Wente, David W. Markby, et al.. (1986). Effect of amino acid substitutions on the catalytic and regulatory properties of aspartate transcarbamoylase.. Proceedings of the National Academy of Sciences. 83(16). 5934–5938. 34 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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