Michael A. Model

1.1k total citations
61 papers, 866 citations indexed

About

Michael A. Model is a scholar working on Molecular Biology, Biophysics and Biomedical Engineering. According to data from OpenAlex, Michael A. Model has authored 61 papers receiving a total of 866 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 26 papers in Biophysics and 14 papers in Biomedical Engineering. Recurrent topics in Michael A. Model's work include Advanced Fluorescence Microscopy Techniques (20 papers), Digital Holography and Microscopy (11 papers) and Cell Image Analysis Techniques (10 papers). Michael A. Model is often cited by papers focused on Advanced Fluorescence Microscopy Techniques (20 papers), Digital Holography and Microscopy (11 papers) and Cell Image Analysis Techniques (10 papers). Michael A. Model collaborates with scholars based in United States, Russia and Germany. Michael A. Model's co-authors include Janis K. Burkhardt, James L. Blank, Priyanka S. Rana, Geneva M. Omann, A. K. Khitrin, Manabu Kurokawa, Laura G. Leff, Valentina E. Yurinskaya, Kevin E. Healy and Ethan Schonbrun and has published in prestigious journals such as PLoS ONE, The Journal of Physiology and Analytical Biochemistry.

In The Last Decade

Michael A. Model

57 papers receiving 855 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 A. Model United States 18 384 272 211 157 119 61 866
Leonel Malacrida Uruguay 21 725 1.9× 481 1.8× 241 1.1× 109 0.7× 94 0.8× 57 1.4k
Nils Norlin Sweden 12 221 0.6× 337 1.2× 173 0.8× 94 0.6× 56 0.5× 19 645
James McGinty United Kingdom 21 465 1.2× 521 1.9× 456 2.2× 84 0.5× 62 0.5× 46 1.4k
Simone Degan United States 21 266 0.7× 115 0.4× 133 0.6× 126 0.8× 202 1.7× 46 990
Wei Ji China 18 725 1.9× 605 2.2× 232 1.1× 85 0.5× 53 0.4× 44 1.4k
Stefan Semrau Netherlands 19 989 2.6× 124 0.5× 164 0.8× 123 0.8× 42 0.4× 32 1.2k
Giuseppe Di Caprio United States 17 462 1.2× 234 0.9× 330 1.6× 490 3.1× 96 0.8× 36 1.4k
Javier Farinas United States 14 1.1k 2.8× 303 1.1× 213 1.0× 62 0.4× 107 0.9× 20 1.6k
Alessandro Ustione United States 22 771 2.0× 311 1.1× 165 0.8× 30 0.2× 103 0.9× 45 1.5k
Per Niklas Hedde United States 19 584 1.5× 409 1.5× 213 1.0× 68 0.4× 76 0.6× 45 1.3k

Countries citing papers authored by Michael A. Model

Since Specialization
Citations

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

Fields of papers citing papers by Michael A. Model

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael A. Model

This figure shows the co-authorship network connecting the top 25 collaborators of Michael A. Model. A scholar is included among the top collaborators of Michael A. Model 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 A. Model. Michael A. Model 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.
Model, Michael A., et al.. (2025). A guide to transport-of-intensity equation (TIE) imaging for biologists. Progress in Biophysics and Molecular Biology. 198. 1–7.
2.
Model, Michael A., et al.. (2024). Measurement of protein concentration in bacteria and small organelles under a light transmission microscope. Journal of Molecular Recognition. 37(5). e3099–e3099. 3 indexed citations
3.
Model, Michael A., et al.. (2022). Nucleic Acids Regulate Intracellular Ions and Membrane Potential. 13–29. 2 indexed citations
4.
Model, Michael A., et al.. (2022). Selective Visualization of Live Intestinal Parasites in Stool Specimens Without Purification. Acta Parasitologica. 67(3). 1455–1459.
5.
Rana, Priyanka S. & Michael A. Model. (2020). A Reverse-Osmosis Model of Apoptotic Shrinkage. Frontiers in Cell and Developmental Biology. 8. 588721–588721. 7 indexed citations
6.
Model, Michael A., et al.. (2020). Macromolecular Crowding: a Hidden Link Between Cell Volume and Everything Else. Cellular Physiology and Biochemistry. 55(S1). 25–40. 31 indexed citations
7.
Model, Michael A., et al.. (2018). Staurosporine-induced apoptotic water loss is cell- and attachment-specific. APOPTOSIS. 23(7-8). 449–455. 10 indexed citations
8.
Rana, Priyanka S., et al.. (2018). Calibration and characterization of intracellular Asante Potassium Green probes, APG-2 and APG-4. Analytical Biochemistry. 567. 8–13. 19 indexed citations
9.
Model, Michael A. & Jonathan C. Petruccelli. (2018). Intracellular Macromolecules in Cell Volume Control and Methods of Their Quantification. Current topics in membranes. 81. 237–289. 15 indexed citations
10.
Kharel, Prakash, et al.. (2016). Volume measurements and fluorescent staining indicate an increase in permeability for organic cation transporter substrates during apoptosis. Experimental Cell Research. 344(1). 112–119. 10 indexed citations
11.
Yurinskaya, Valentina E., et al.. (2014). Computation of Pump-Leak Flux Balance in Animal Cells. Cellular Physiology and Biochemistry. 34(5). 1812–1823. 18 indexed citations
12.
Khitrin, A. K., et al.. (2014). A model for membrane potential and intracellular ion distribution. Chemistry and Physics of Lipids. 184. 76–81. 14 indexed citations
13.
Kuželová, Kateřina, et al.. (2013). Live fluorescence and transmission-through-dye microscopic study of actinomycin D-induced apoptosis and apoptotic volume decrease. APOPTOSIS. 18(4). 521–532. 29 indexed citations
14.
Model, Michael A. & Ethan Schonbrun. (2013). Optical determination of intracellular water in apoptotic cells. The Journal of Physiology. 591(23). 5843–5849. 28 indexed citations
15.
Gregg, Jennifer L., et al.. (2010). Measurement of the thickness and volume of adherent cells using transmission-through-dye microscopy. Pflügers Archiv - European Journal of Physiology. 460(6). 1097–1104. 34 indexed citations
16.
Model, Michael A., et al.. (2009). Measurement of wheat germ agglutinin binding with a fluorescence microscope. Cytometry Part A. 75A(10). 874–881. 21 indexed citations
17.
Model, Michael A. & James L. Blank. (2007). Concentrated dyes as a source of two‐dimensional fluorescent field for characterization of a confocal microscope. Journal of Microscopy. 229(1). 12–16. 16 indexed citations
18.
Model, Michael A. & Janis K. Burkhardt. (2001). A standard for calibration and shading correction of a fluorescence microscope. Cytometry. 44(4). 309–316. 94 indexed citations
19.
Model, Michael A. & Geneva M. Omann. (1998). EXPERIMENTAL APPROACHES FOR OBSERVING HOMOLOGOUS DESENSITISATION AND THEIR PITFALLS. Pharmacological Research. 37(4). 285–288. 3 indexed citations
20.
Model, Michael A. & Geneva M. Omann. (1996). Cell Polarization as a Possible Mechanism of Response Termination. Biochemical and Biophysical Research Communications. 224(2). 516–521. 4 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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