Matthias P. Machner

2.8k citations
34 papers · 2.1k indexed · h-index 19

Matthias P. Machner

34 papers receiving 2.0k citations

Peers

Matthias P. Machner
Comparison fields: 5 of 89
  • Endocrinology 991
  • Cell Biology 458
  • Immunology 527
  • Physiology 99
  • Biotechnology 150
Replace Mauricio R. Terebiznik with:
Mauricio R. Terebiznik Canada
Shaeri Mukherjee United States
Raymond Hellio France
Jörg Selzer Germany
Jonathan N. Pruneda United States
Frédéric Mallard France
Mohammed Benghezal Australia
Alejandro P. Heuck United States
Walter Berón Argentina
André Catic United States
Matthias P. Machner relative to Mauricio R. Terebiznik Canada Mauricio R. Terebiznik's profile →
Citations per field
00.5×1.5×2.4×
Mauricio R. Terebiznik · 1×
Citations per year

Countries citing papers authored by Matthias P. Machner

Since Specialization
Citations

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

Fields of papers citing papers by Matthias P. Machner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthias P. Machner. 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 Matthias P. Machner. The network helps show where Matthias P. Machner may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Matthias P. Machner, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Matthias P. Machner Line = papers co-authored together Matthias P. Machner links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20242
2 20231
3 20237
4 202118
5 20206
6 201846
7 201814
8 201832
9 201733
10 201551
11 201439
12 201325
13 2011187
14 20113
15 2010147
16 2007180
17 2006285
18 200423
19 2002235
20 200127

About Matthias P. Machner

Matthias P. Machner is a scholar working on Endocrinology, Biotechnology and Pediatrics, Perinatology and Child Health, having authored 34 papers that have together received 2.1k indexed citations. Recurring topics across this work include Legionella and Acanthamoeba research (23 papers), Neonatal Health and Biochemistry (8 papers), Vibrio bacteria research studies (7 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (7 papers), Bacterial biofilms and quorum sensing (6 papers), Biomedical Research and Pathophysiology (5 papers), Autophagy in Disease and Therapy (4 papers) and Heme Oxygenase-1 and Carbon Monoxide (4 papers). The work is most often cited by research in Endocrinology (991 citations), Cell Biology (458 citations) and Immunology (527 citations). Matthias P. Machner has collaborated with scholars based in United States, Spain and Germany. Frequent co-authors include Ralph R. Isberg, Tamás Balla, Gerald Hammond, Andrew H. Gaspar, M. Ramona Neunuebel, Yi‐Han Lin, Chen Yang, Dirk W. Heinz, Wolf‐Dieter Schubert and Jürgen Wehland. Their work appears in journals such as Proceedings of the National Academy of Sciences, PLoS Pathogens, Science, Journal of Biological Chemistry and eLife.

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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