Jan Mach

539 total citations
36 papers, 358 citations indexed

About

Jan Mach is a scholar working on Molecular Biology, Epidemiology and Endocrinology. According to data from OpenAlex, Jan Mach has authored 36 papers receiving a total of 358 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 7 papers in Epidemiology and 6 papers in Endocrinology. Recurrent topics in Jan Mach's work include Trypanosoma species research and implications (7 papers), Legionella and Acanthamoeba research (6 papers) and Heme Oxygenase-1 and Carbon Monoxide (5 papers). Jan Mach is often cited by papers focused on Trypanosoma species research and implications (7 papers), Legionella and Acanthamoeba research (6 papers) and Heme Oxygenase-1 and Carbon Monoxide (5 papers). Jan Mach collaborates with scholars based in Czechia, France and United States. Jan Mach's co-authors include Róbert Šuťák, Jan Tachezy, Eva Nývltová, Emmanuel Lesuisse, Julius Lukeš, Jean‐Michel Camadro, Jan Pačes, Courtney W. Stairs, Andrew J. Roger and Elena Kazamia and has published in prestigious journals such as PLoS ONE, Antimicrobial Agents and Chemotherapy and Science Advances.

In The Last Decade

Jan Mach

31 papers receiving 351 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan Mach Czechia 12 177 89 69 64 52 36 358
Guohui Xiao China 10 133 0.8× 50 0.6× 47 0.7× 48 0.8× 57 1.1× 23 307
Marie-Françoise Liaud Germany 7 283 1.6× 117 1.3× 42 0.6× 44 0.7× 57 1.1× 7 425
Natalie D. King United States 12 215 1.2× 44 0.5× 21 0.3× 21 0.3× 9 0.2× 12 418
Sébastien Brûlé France 12 154 0.9× 56 0.6× 44 0.6× 15 0.2× 44 0.8× 21 358
Loic Bærlocher Switzerland 10 364 2.1× 148 1.7× 132 1.9× 36 0.6× 14 0.3× 14 704
Kacper Sendra United Kingdom 9 207 1.2× 95 1.1× 19 0.3× 10 0.2× 138 2.7× 13 406
José A. Fernández‐Robledo United States 8 168 0.9× 93 1.0× 21 0.3× 10 0.2× 84 1.6× 10 395
Julie D. Gauthier United States 14 152 0.9× 307 3.4× 14 0.2× 57 0.9× 152 2.9× 18 623
Jiří Vávra Czechia 10 76 0.4× 76 0.9× 113 1.6× 27 0.4× 86 1.7× 20 363
Stefania Domeneghetti Italy 8 79 0.4× 40 0.4× 11 0.2× 18 0.3× 22 0.4× 11 307

Countries citing papers authored by Jan Mach

Since Specialization
Citations

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

Fields of papers citing papers by Jan Mach

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Mach

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Mach. A scholar is included among the top collaborators of Jan 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 Jan Mach. Jan 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.
Folgosa, Filipe, Libor Mikeš, Jan Mach, et al.. (2025). Eating the brain - A multidisciplinary study provides new insights into the mechanisms underlying the cytopathogenicity of Naegleria fowleri. PLoS Pathogens. 21(3). e1012995–e1012995. 1 indexed citations
2.
Stopka, Pavel, Guillaume Chevreux, Jan Mach, et al.. (2025). Molecular Mechanisms of Acanthamoeba castellanii Response to Different Sources of Oxidative Stress. Journal of Proteome Research. 24(2). 449–458. 2 indexed citations
3.
Mach, Jan, Jan Štursa, Marta Machado, et al.. (2024). Chelation of Mitochondrial Iron as an Antiparasitic Strategy. ACS Infectious Diseases. 10(2). 676–687. 3 indexed citations
4.
Mach, Jan, et al.. (2023). The 4-Aminomethylphenoxy-Benzoxaborole AN3057 as a Potential Treatment Option for Primary Amoebic Meningoencephalitis. Antimicrobial Agents and Chemotherapy. 67(2). e0150622–e0150622. 3 indexed citations
5.
Mach, Jan, et al.. (2022). Elucidation of iron homeostasis in Acanthamoeba castellanii. International Journal for Parasitology. 52(8). 497–508. 4 indexed citations
6.
Mach, Jan, et al.. (2021). How to Prevent Plagiarism in Student Work. 1 indexed citations
7.
Stopka, Pavel, et al.. (2021). Flow cytometry-based study of model marine microalgal consortia revealed an ecological advantage of siderophore utilization by the dinoflagellate Amphidinium carterae. Computational and Structural Biotechnology Journal. 20. 287–295. 4 indexed citations
8.
Žárský, Vojtěch, Vladimír Klimeš, Jan Pačes, et al.. (2021). The Mastigamoeba balamuthi Genome and the Nature of the Free-Living Ancestor of Entamoeba. Molecular Biology and Evolution. 38(6). 2240–2259. 17 indexed citations
9.
Mach, Jan, et al.. (2020). Copper detoxification machinery of the brain-eating amoeba Naegleria fowleri involves copper-translocating ATPase and the antioxidant system. International Journal for Parasitology Drugs and Drug Resistance. 14. 126–135. 12 indexed citations
10.
Mach, Jan, et al.. (2020). Adaptive iron utilization compensates for the lack of an inducible uptake system in Naegleria fowleri and represents a potential target for therapeutic intervention. PLoS neglected tropical diseases. 14(6). e0007759–e0007759. 16 indexed citations
11.
Mach, Jan, et al.. (2018). Iron economy in Naegleria gruberi reflects its metabolic flexibility. International Journal for Parasitology. 48(9-10). 719–727. 16 indexed citations
12.
Peña‐Diaz, Priscila, et al.. (2018). Trypanosomal mitochondrial intermediate peptidase does not behave as a classical mitochondrial processing peptidase. PLoS ONE. 13(4). e0196474–e0196474. 7 indexed citations
13.
Kazamia, Elena, Róbert Šuťák, Javier Paz-Yepes, et al.. (2018). Endocytosis-mediated siderophore uptake as a strategy for Fe acquisition in diatoms. Science Advances. 4(5). eaar4536–eaar4536. 78 indexed citations
14.
Mach, Jan, et al.. (2017). Nonlinear Galerkin finite element method applied to the system of reaction–diffusion equations in one space dimension. Computers & Mathematics with Applications. 73(9). 2053–2065. 7 indexed citations
15.
Nývltová, Eva, Courtney W. Stairs, Ivan Hrdý, et al.. (2015). Lateral Gene Transfer and Gene Duplication Played a Key Role in the Evolution of Mastigamoeba balamuthi Hydrogenosomes. Molecular Biology and Evolution. 32(4). 1039–1055. 45 indexed citations
16.
17.
Mach, Jan, Jan Tachezy, & Róbert Šuťák. (2013). Efficient Iron Uptake via a Reductive Mechanism in ProcyclicTrypanosoma brucei. Journal of Parasitology. 99(2). 363–364. 17 indexed citations
18.
Long, Shaojun, Milan Jirků, Jan Mach, et al.. (2008). Ancestral roles of eukaryotic frataxin: mitochondrial frataxin function and heterologous expression of hydrogenosomal Trichomonas homologues in trypanosomes. Molecular Microbiology. 69(1). 94–109. 34 indexed citations
19.
Mach, Jan. (2004). On optimality conditions of relaxed non-convex variational problems. Journal of Mathematical Analysis and Applications. 298(1). 157–170.
20.
Mach, Jan. (2004). Finite Element Analysis of Free Material Optimization Problem. Applications of Mathematics. 49(4). 285–307. 1 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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