Markus Franz

1.4k total citations · 1 hit paper
8 papers, 1.2k citations indexed

About

Markus Franz is a scholar working on Computer Vision and Pattern Recognition, Biotechnology and Immunology. According to data from OpenAlex, Markus Franz has authored 8 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Computer Vision and Pattern Recognition, 2 papers in Biotechnology and 2 papers in Immunology. Recurrent topics in Markus Franz's work include Plant Parasitism and Resistance (2 papers), Transgenic Plants and Applications (2 papers) and Toxin Mechanisms and Immunotoxins (2 papers). Markus Franz is often cited by papers focused on Plant Parasitism and Resistance (2 papers), Transgenic Plants and Applications (2 papers) and Toxin Mechanisms and Immunotoxins (2 papers). Markus Franz collaborates with scholars based in Germany. Markus Franz's co-authors include Tobias Dezulian, Daniel H. Huson, Daniel C. Richter, Regula Rupp, Christian Rausch, Oliver Hinz, Michael Scholz, Deborah Robinson, Robin M. Warren and Verena Dorner and has published in prestigious journals such as Journal of Clinical Microbiology, BMC Bioinformatics and Decision Support Systems.

In The Last Decade

Markus Franz

8 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Dendroscope: An interactive viewer for large phylogenetic trees

2007 1.0k citations Daniel H. Huson, Daniel C. Richter et al. BMC Bioinformatics profile →

Peers

Markus Franz

MB

PS

GENET

ECOLO

EEBS

Richard McVeigh United States

Greg Von Kuster Germany

Daniel C. Richter Germany

Carl Eberhard United States

Fourie Joubert South Africa

Matt Pearce United Kingdom

Lydia Steiner Germany

Paolo Di Tommaso Spain

Brigitte Schaeffer France

Delphine Naquin France

Richard McVeigh United States

Markus Franz

912 ×1.6

MB

224 ×0.8

PS

181 ×1.1

GENET

347 ×2.1

ECOLO

67 ×0.6

EEBS

Citations per year, relative to Markus Franz Markus Franz (= 1×) peers Richard McVeigh

Countries citing papers authored by Markus Franz

Since Specialization

Citations

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

Fields of papers citing papers by Markus Franz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Markus Franz

This figure shows the co-authorship network connecting the top 25 collaborators of Markus Franz. A scholar is included among the top collaborators of Markus Franz 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 Franz. Markus Franz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Scholz, Michael, Markus Franz, & Oliver Hinz. (2017). Effects of decision space information on MAUT-based systems that support purchase decision processes. Decision Support Systems. 97. 43–57. 15 indexed citations

2.

Scholz, Michael, Markus Franz, & Oliver Hinz. (2016). The Ambiguous Identifier Clustering Technique. Electronic Markets. 26(2). 143–156. 5 indexed citations

3.

Wichtlhuber, Matthias, et al.. (2016). Are incentive schemes needed for WebRTC based distributed streaming?. TUbilio (Technical University of Darmstadt). 1–12. 4 indexed citations

4.

Scholz, Michael, Verena Dorner, Markus Franz, & Oliver Hinz. (2015). Measuring consumers' willingness to pay with utility-based recommendation systems. Decision Support Systems. 72. 60–71. 36 indexed citations

5.

Huson, Daniel H., Daniel C. Richter, Christian Rausch, et al.. (2007). Dendroscope: An interactive viewer for large phylogenetic trees. BMC Bioinformatics. 8(1). 460–460. 1034 indexed citations breakdown →

6.

Klein, Reinhild, et al.. (2004). Demonstration of antibodies to the chitin-binding mistletoe lectin (cbML) in tumor patients before and during therapy with an aqueous mistletoe extract.. PubMed. 9(6). 316–22. 4 indexed citations

7.

Voelter, Wolfgang, et al.. (2000). Complete Structural Characterization of a Chitin-Binding Lectin from Mistletoe Extracts. Journal für praktische Chemie. 342(8). 812–818. 7 indexed citations

8.

Robinson, Deborah, et al.. (1982). Detection by enzyme-linked immunosorbent assays of antibody specific for Pseudomonas proteases and exotoxin A in sera from cystic fibrosis patients. Journal of Clinical Microbiology. 15(6). 1054–1058. 49 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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