Michael J. Chapman

2.9k total citations
20 papers, 453 citations indexed

About

Michael J. Chapman is a scholar working on Molecular Biology, Control and Systems Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Michael J. Chapman has authored 20 papers receiving a total of 453 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Control and Systems Engineering and 3 papers in Computational Theory and Mathematics. Recurrent topics in Michael J. Chapman's work include Advanced Control Systems Optimization (5 papers), Analytical Chemistry and Chromatography (2 papers) and Cosmology and Gravitation Theories (2 papers). Michael J. Chapman is often cited by papers focused on Advanced Control Systems Optimization (5 papers), Analytical Chemistry and Chromatography (2 papers) and Cosmology and Gravitation Theories (2 papers). Michael J. Chapman collaborates with scholars based in United Kingdom, United States and Canada. Michael J. Chapman's co-authors include Lynn Margulis, K.R. Godfrey, Michael J. Chappell, Neil D. Evans, Michael F. Dolan, Sándor Vajda, Lisa J. White, Paul J. Smith, Rachel J. Errington and Stephen B. Duffull and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, Trends in Microbiology and The Quarterly Review of Biology.

In The Last Decade

Michael J. Chapman

20 papers receiving 432 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael J. Chapman United Kingdom 13 153 46 46 41 39 20 453
I-Chun Chou United States 8 538 3.5× 60 1.3× 13 0.3× 10 0.2× 24 0.6× 10 660
Hiroaki Hara Japan 13 97 0.6× 4 0.1× 60 1.3× 20 0.5× 12 0.3× 75 621
Thomas Cokelaer France 19 747 4.9× 25 0.5× 14 0.3× 25 0.6× 124 3.2× 44 1.3k
Evgeni V. Nikolaev United States 13 587 3.8× 36 0.8× 16 0.3× 8 0.2× 11 0.3× 28 902
Marco Antônio Teixeira Brazil 25 24 0.2× 181 3.9× 30 0.7× 38 0.9× 22 0.6× 119 1.9k
S. Parthasarathy India 14 114 0.7× 9 0.2× 19 0.4× 6 0.1× 21 0.5× 45 580
David B. Bernstein United States 10 320 2.1× 5 0.1× 16 0.3× 11 0.3× 20 0.5× 16 581
Carolus J. Reinecke South Africa 17 343 2.2× 8 0.2× 9 0.2× 38 0.9× 30 0.8× 42 697
David Iron Canada 13 108 0.7× 35 0.8× 135 2.9× 29 0.7× 18 0.5× 33 639
Florent Malrieu France 14 89 0.6× 28 0.6× 80 1.7× 2 0.0× 14 0.4× 22 623

Countries citing papers authored by Michael J. Chapman

Since Specialization
Citations

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

Fields of papers citing papers by Michael J. Chapman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael J. Chapman. 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 Michael J. Chapman. The network helps show where Michael J. Chapman may publish in the future.

Co-authorship network of co-authors of Michael J. Chapman

This figure shows the co-authorship network connecting the top 25 collaborators of Michael J. Chapman. A scholar is included among the top collaborators of Michael J. Chapman 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 Michael J. Chapman. Michael J. Chapman 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.
Chapman, Michael J., Zhongxu Zhai, & Will J. Percival. (2023). Isolating the linear signal when making redshift space distortion measurements. Monthly Notices of the Royal Astronomical Society. 525(2). 2135–2153. 4 indexed citations
2.
Chapman, Michael J., Faizan G Mohammad, Zhongxu Zhai, et al.. (2022). The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: measurement of the growth rate of structure from the small-scale clustering of the luminous red galaxy sample. Monthly Notices of the Royal Astronomical Society. 516(1). 617–635. 20 indexed citations
3.
Margulis, Lynn & Michael J. Chapman. (2009). Kingdoms & domains : an illustrated guide to the phyla of life on Earth. Medical Entomology and Zoology. 16 indexed citations
4.
Margulis, Lynn, et al.. (2009). Spirochete round bodies Syphilis, Lyme disease & AIDS: Resurgence of “the great imitator”?. Symbiosis. 47(1). 51–58. 16 indexed citations
5.
Evans, Neil D., Lisa J. White, Michael J. Chapman, K.R. Godfrey, & Michael J. Chappell. (2005). The structural identifiability of the susceptible infected recovered model with seasonal forcing. Mathematical Biosciences. 194(2). 175–197. 39 indexed citations
6.
Evans, Neil D., Rachel J. Errington, Michael J. Chapman, et al.. (2005). Compartmental modelling of the uptake kinetics of the anti‐cancer agent topotecan in human breast cancer cells. International Journal of Adaptive Control and Signal Processing. 19(5). 395–417. 12 indexed citations
7.
Evans, Neil D., Rachel J. Errington, M. Shelley, et al.. (2004). A mathematical model for the in vitro kinetics of the anti-cancer agent topotecan. Mathematical Biosciences. 189(2). 185–217. 30 indexed citations
8.
Chapman, Michael J., K.R. Godfrey, Michael J. Chappell, & Neil D. Evans. (2003). Structural identifiability for a class of non-linear compartmental systems using linear/non-linear splitting and symbolic computation. Mathematical Biosciences. 183(1). 1–14. 26 indexed citations
9.
Godfrey, K.R., et al.. (2001). An Identifiability Analysis of a Parent–Metabolite Pharmacokinetic Model for Ivabradine. Journal of Pharmacokinetics and Pharmacodynamics. 28(1). 93–105. 32 indexed citations
10.
Chapman, Michael J., Michael F. Dolan, & Lynn Margulis. (2000). Centrioles and Kinetosomes: Form, Function, and Evolution. The Quarterly Review of Biology. 75(4). 409–429. 43 indexed citations
11.
Chapman, Michael J.. (1998). One hundred years of centrioles: the Henneguy-Lenhossek theory, meeting report.. PubMed. 1(3). 233–6. 3 indexed citations
12.
Margulis, Lynn & Michael J. Chapman. (1998). Endosymbioses: cyclical and permanent in evolution. Trends in Microbiology. 6(9). 342–345. 64 indexed citations
13.
Chapman, Michael J. & Lynn Margulis. (1998). Morphogenesis by symbiogenesis.. PubMed. 1(4). 319–26. 42 indexed citations
14.
Chapman, Michael J., et al.. (1997). Signal processing in electronic communications. Woodhead Publishing Limited eBooks. 1 indexed citations
15.
Chapman, Michael J., K.R. Godfrey, & Sándor Vajda. (1994). Indistinguishability for a class of nonlinear compartmental models. Mathematical Biosciences. 119(1). 77–95. 9 indexed citations
16.
Godfrey, K.R., Michael J. Chapman, & Sándor Vajda. (1994). Identifiability and indistinguishability of nonlinear pharmacokinetic models. Journal of Pharmacokinetics and Biopharmaceutics. 22(3). 229–251. 26 indexed citations
17.
Godfrey, K.R. & Michael J. Chapman. (1990). Identifiability and indistinguishability of linear compartmental models. Mathematics and Computers in Simulation. 32(3). 273–295. 31 indexed citations
18.
Godfrey, K.R. & Michael J. Chapman. (1989). The problem of model indistinguishability in pharmacokinetics. Journal of Pharmacokinetics and Biopharmaceutics. 17(2). 229–267. 17 indexed citations
19.
Chapman, Michael J. & K.R. Godfrey. (1989). A methodology for compartmental model indistinguishability. Mathematical Biosciences. 96(2). 141–164. 10 indexed citations
20.
Chapman, Michael J. & K.R. Godfrey. (1985). Some extensions to the exhaustive-modeling approach to structural identifiability. Mathematical Biosciences. 77(1-2). 305–323. 12 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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