Markus Ackermann

688 total citations
38 papers, 484 citations indexed

About

Markus Ackermann is a scholar working on Ecology, Evolution, Behavior and Systematics, Molecular Biology and Epidemiology. According to data from OpenAlex, Markus Ackermann has authored 38 papers receiving a total of 484 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Ecology, Evolution, Behavior and Systematics, 9 papers in Molecular Biology and 9 papers in Epidemiology. Recurrent topics in Markus Ackermann's work include Plant Diversity and Evolution (12 papers), Plant and animal studies (9 papers) and Animal Disease Management and Epidemiology (7 papers). Markus Ackermann is often cited by papers focused on Plant Diversity and Evolution (12 papers), Plant and animal studies (9 papers) and Animal Disease Management and Epidemiology (7 papers). Markus Ackermann collaborates with scholars based in Germany, Switzerland and Belgium. Markus Ackermann's co-authors include Maximilian Weigend, Robert Wyler, Ernst Peterhans, Tilo Henning, R. J. Whitley, Fred D. Lakeman, J B Kahlon, Stefan Abrahamczyk, Eberhard Fischer and V. Bitsch and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Physics Letters and PLoS ONE.

In The Last Decade

Markus Ackermann

36 papers receiving 447 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Markus Ackermann Germany 12 263 175 106 104 90 38 484
Richard Carter United States 15 169 0.6× 88 0.5× 154 1.5× 51 0.5× 227 2.5× 22 1.0k
Barbara J. Ruef United States 13 74 0.3× 80 0.5× 16 0.2× 36 0.3× 228 2.5× 21 478
Daniel B. Weissman United States 12 69 0.3× 56 0.3× 13 0.1× 46 0.4× 200 2.2× 27 587
Rachel Robinson Australia 8 115 0.4× 484 2.8× 94 0.9× 8 0.1× 80 0.9× 9 669
Jennifer Chapman United States 15 56 0.2× 428 2.4× 25 0.2× 70 0.7× 374 4.2× 25 956
David V. Jobes United States 16 82 0.3× 198 1.1× 8 0.1× 269 2.6× 364 4.0× 25 1.2k
Yee‐Peng Chan United States 12 163 0.6× 989 5.7× 143 1.3× 16 0.2× 240 2.7× 14 1.2k
Christian Hertig Germany 13 156 0.6× 149 0.9× 187 1.8× 198 1.9× 188 2.1× 26 603
Yao E. Wang United States 9 58 0.2× 308 1.8× 32 0.3× 36 0.3× 133 1.5× 9 535
S. A. Hill United States 12 182 0.7× 72 0.4× 204 1.9× 201 1.9× 96 1.1× 27 620

Countries citing papers authored by Markus Ackermann

Since Specialization
Citations

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

Fields of papers citing papers by Markus Ackermann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Markus Ackermann

This figure shows the co-authorship network connecting the top 25 collaborators of Markus Ackermann. A scholar is included among the top collaborators of Markus Ackermann 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 Markus Ackermann. Markus Ackermann 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.
Ackermann, Markus, et al.. (2020). MMoOn Core – the Multilingual Morpheme Ontology. Semantic Web. 12(5). 813–841. 2 indexed citations
2.
Weigend, Maximilian, et al.. (2018). Breeding systems in Balsaminaceae in relation to pollen/ovule ratio, pollination syndromes, life history and climate zone. Plant Biology. 21(1). 157–166. 23 indexed citations
3.
Abrahamczyk, Stefan, et al.. (2017). A question of data quality—Testing pollination syndromes in Balsaminaceae. PLoS ONE. 12(10). e0186125–e0186125. 20 indexed citations
4.
Hellmann, Sebastian, et al.. (2016). FREME: Multilingual Semantic Enrichment with Linked Data and Language Technologies.. Language Resources and Evaluation. 4180–4183.
5.
Ackermann, Markus, et al.. (2015). Knowledge base shipping to the linked open data cloud. 73–80. 3 indexed citations
6.
Moussallem, Diego, et al.. (2015). MEX vocabulary. Zenodo (CERN European Organization for Nuclear Research). 169–176. 23 indexed citations
7.
Ackermann, Markus, et al.. (2008). Hybridization and crossability in Caiophora (Loasaceae subfam. Loasoideae): Are interfertile species and inbred populations results of a recent radiation?. American Journal of Botany. 95(9). 1109–1121. 14 indexed citations
8.
Ackermann, Markus & Maximilian Weigend. (2007). Notes on the genus Caiophora (Loasoideae, Loasaceae) in Chile and neighbouring countries. SHILAP Revista de lepidopterología. 4 indexed citations
9.
Ackermann, Markus, Bettina Berendt, Marko Grobelnik, et al.. (2007). Semantics, Web and Mining: Joint International Workshop, EWMF 2005 and KDO 2005, Porto, Portugal, October 3-7, 2005, Revised Selected Papers (Lecture Notes in Computer Science). Springer eBooks. 125(9). 1153–5. 2 indexed citations
10.
Bast, Holger, Georges Dupret, Debapriyo Majumdar, et al.. (2006). Discovering a Term Taxonomy from Term Similarities Using Principal Component Analysis. Lecture notes in computer science. 103–120. 2 indexed citations
11.
Ackermann, Markus & Maximilian Weigend. (2006). Nectar, Floral Morphology and Pollination Syndrome in Loasaceae subfam. Loasoideae (Cornales). Annals of Botany. 98(3). 503–514. 49 indexed citations
12.
Ackermann, Markus, et al.. (2006). Semantics, Web and Mining. Lecture notes in computer science. 13 indexed citations
13.
Ackermann, Markus, et al.. (2005). Conceptual Taxonomy Identification in Medical Documents. Data Archiving and Networked Services (DANS). 31–38. 5 indexed citations
14.
Grob, Philipp, Andreas J. Hülsmeier, Uwe Mueller-Doblies, et al.. (2004). The humoral and cellular immune response of sheep against Borna disease virus in endemic and non-endemic areas. Schweizer Archiv für Tierheilkunde. 146(4). 159–172. 2 indexed citations
15.
Ackermann, Markus, et al.. (1994). [Comparison of two ELISA systems for the detection of antibodies against IBR/IPV and against enzootic bovine leukemia virus].. PubMed. 136(2). 58–67. 7 indexed citations
16.
Ackermann, Markus, Sándor Bélak, V. Bitsch, et al.. (1990). Round table on infectious bovine rhinotracheitis/ infectious pustular vulvovaginitis virus infection diagnosis and control. Veterinary Microbiology. 23(1-4). 361–363. 39 indexed citations
17.
Villinger, François, et al.. (1989). Antibodies to foot-and-mouth disease virus infection associated (VIA) antigen: Use of a bioengineered VIA protein as antigen in an ELISA. Veterinary Microbiology. 20(3). 235–246. 21 indexed citations
18.
Villinger, François, et al.. (1989). [The effectiveness of foot-and-mouth disease vaccines in Switzerland. I. Screening tests and herd immunity].. PubMed. 131(7). 379–86. 1 indexed citations
19.
Spirig, Christian, et al.. (1987). [Dried whole blood on filter discs for the detection of IBR/IPV antibodies in ELISA].. PubMed. 129(10). 529–35. 3 indexed citations
20.
Ackermann, Markus, Ernst Peterhans, & Robert Wyler. (1982). DNA of Bovine Herpesvirus Type 1 in the Trigeminal Ganglia of Latently Infected Calves. American Journal of Veterinary Research. 43(1). 36–40. 107 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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