Michael Mach

6.2k total citations · 1 hit paper
105 papers, 4.9k citations indexed

About

Michael Mach is a scholar working on Epidemiology, Parasitology and Immunology. According to data from OpenAlex, Michael Mach has authored 105 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 90 papers in Epidemiology, 33 papers in Parasitology and 25 papers in Immunology. Recurrent topics in Michael Mach's work include Cytomegalovirus and herpesvirus research (90 papers), Herpesvirus Infections and Treatments (64 papers) and Toxoplasma gondii Research Studies (32 papers). Michael Mach is often cited by papers focused on Cytomegalovirus and herpesvirus research (90 papers), Herpesvirus Infections and Treatments (64 papers) and Toxoplasma gondii Research Studies (32 papers). Michael Mach collaborates with scholars based in Germany, United States and Sweden. Michael Mach's co-authors include William J. Britt, Barbara Kropff, Suresh B. Boppana, Karen B. Fowler, Lisa B. Rivera, Thomas Winkler, Gerhard Jahn, Ursula Utz, Magdalena A. Krzyzaniak and Mats Ohlin and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Michael Mach

102 papers receiving 4.7k citations

Hit Papers

Intrauterine Transmission of Cytomegalovirus to Infants o... 2001 2026 2009 2017 2001 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Mach Germany 44 4.1k 1.2k 1.0k 906 540 105 4.9k
Teresa Compton United States 29 2.9k 0.7× 648 0.5× 575 0.6× 1.5k 1.7× 785 1.5× 45 4.0k
Michael A. Jarvis United States 30 2.7k 0.7× 571 0.5× 1.1k 1.1× 1.5k 1.6× 592 1.1× 70 4.3k
Mark R. Wills United Kingdom 42 3.3k 0.8× 607 0.5× 666 0.6× 2.9k 3.2× 1.0k 1.9× 114 5.8k
Michael A. McVoy United States 31 1.9k 0.5× 396 0.3× 482 0.5× 352 0.4× 307 0.6× 94 2.2k
Mark F. Stinski United States 48 6.0k 1.5× 1.5k 1.3× 402 0.4× 1.5k 1.7× 2.4k 4.4× 106 7.0k
Barry Slobedman Australia 39 2.7k 0.7× 598 0.5× 349 0.3× 1.7k 1.9× 453 0.8× 93 3.7k
Lucy Rasmussen United States 29 2.1k 0.5× 548 0.5× 295 0.3× 506 0.6× 239 0.4× 49 2.5k
Allison Abendroth Australia 36 2.4k 0.6× 543 0.5× 277 0.3× 1.4k 1.6× 376 0.7× 79 3.3k
Emma Poole United Kingdom 31 1.9k 0.5× 435 0.4× 343 0.3× 873 1.0× 570 1.1× 63 2.5k
Patricia P. Smith United States 27 1.7k 0.4× 316 0.3× 327 0.3× 493 0.5× 636 1.2× 45 2.6k

Countries citing papers authored by Michael Mach

Since Specialization
Citations

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

Fields of papers citing papers by Michael Mach

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Mach

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Mach. A scholar is included among the top collaborators of Michael Mach 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 Mach. Michael Mach 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.
Reuter, Nina, Barbara Kropff, Xiaohan Chen, et al.. (2024). The Autonomous Fusion Activity of Human Cytomegalovirus Glycoprotein B Is Regulated by Its Carboxy-Terminal Domain. Viruses. 16(9). 1482–1482. 1 indexed citations
2.
Reuter, Nina, et al.. (2024). Functional Fc receptors are crucial in antibody‐mediated protection against cytomegalovirus. European Journal of Immunology. 54(10). e2451044–e2451044.
4.
Büttner‐Herold, Maike, Petra Hoffmann, Matthias Edinger, et al.. (2023). Murine cytomegalovirus reactivation concomitant with acute graft-versus-host disease is controlled by antibodies. JCI Insight. 8(5). 1 indexed citations
6.
Baraniak, Ilona, Barbara Kropff, Gary R. McLean, et al.. (2018). Epitope-Specific Humoral Responses to Human Cytomegalovirus Glycoprotein-B Vaccine With MF59: Anti-AD2 Levels Correlate With Protection From Viremia. The Journal of Infectious Diseases. 217(12). 1907–1917. 46 indexed citations
7.
Kropff, Barbara, Nina Reuter, Heinrich Sticht, et al.. (2017). Protective capacity of neutralizing and non-neutralizing antibodies against glycoprotein B of cytomegalovirus. PLoS Pathogens. 13(8). e1006601–e1006601. 81 indexed citations
8.
Kropff, Barbara, et al.. (2012). Glycoprotein N of Human Cytomegalovirus Protects the Virus from Neutralizing Antibodies. PLoS Pathogens. 8(10). e1002999–e1002999. 39 indexed citations
9.
Sampaio, Kerstin Laib, Nicole Ettischer, York‐Dieter Stierhof, et al.. (2011). UL74 of human cytomegalovirus reduces the inhibitory effect of gH-specific and gB-specific antibodies. Archives of Virology. 156(12). 2145–2155. 22 indexed citations
10.
Full, Florian, Manfred Lehner, Veronika Thonn, et al.. (2010). T Cells Engineered with a Cytomegalovirus-Specific Chimeric Immunoreceptor. Journal of Virology. 84(8). 4083–4088. 42 indexed citations
11.
Spaderna, Simone, Barbara Kropff, Siyuan Shen, et al.. (2005). Deletion of gpUL132, a Structural Component of Human Cytomegalovirus, Results in Impaired Virus Replication in Fibroblasts. Journal of Virology. 79(18). 11837–11847. 24 indexed citations
12.
Rohwer, Peter, et al.. (2004). Activation of Virus-specific Memory B Cells in the Absence of T Cell Help. The Journal of Experimental Medicine. 199(4). 593–602. 96 indexed citations
13.
Falk, Christine S., Michael Mach, Dolores J. Schendel, et al.. (2002). NK Cell Activity During Human Cytomegalovirus Infection Is Dominated by US2–11-Mediated HLA Class I Down-Regulation. The Journal of Immunology. 169(6). 3257–3266. 72 indexed citations
14.
Mach, Michael, et al.. (2000). Dense Bodies of Human Cytomegalovirus Induce both Humoral and Cellular Immune Responses in the Absence of Viral Gene Expression. Journal of Virology. 74(13). 6132–6146. 89 indexed citations
15.
Kropff, Barbara, et al.. (1997). The Humoral Immune Response against Human Cytomegalovirus Is Characterized by a Delayed Synthesis of Glycoprotein-Specific Antibodies. The Journal of Infectious Diseases. 175(3). 533–544. 93 indexed citations
16.
Britt, William J. & Michael Mach. (1996). Human Cytomegalovirus Glycoproteins. Intervirology. 39(5-6). 401–412. 155 indexed citations
18.
Masuho, Yasuhiko, et al.. (1990). The gp116 of the gp58/116 complex of human cytomegalovirus represents the amino-terminal part of the precursor molecule and contains a neutralizing epitope. Journal of General Virology. 71(10). 2443–2450. 70 indexed citations
19.
Jahn, Gerhard & Michael Mach. (1990). Human Cytomegalovirus Phosphoproteins and Glycoproteins and Their Coding Regions. Current topics in microbiology and immunology. 154. 171–185. 18 indexed citations
20.
Mach, Michael, Thomas Stamminger, & Gerhard Jahn. (1989). Human Cytomegalovirus: Recent Aspects from Molecular Biology. Journal of General Virology. 70(12). 3117–3146. 39 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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