Nina Luhmann

1.4k total citations · 2 hit papers
8 papers, 809 citations indexed

About

Nina Luhmann is a scholar working on Molecular Biology, Genetics and Plant Science. According to data from OpenAlex, Nina Luhmann has authored 8 papers receiving a total of 809 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 5 papers in Genetics and 4 papers in Plant Science. Recurrent topics in Nina Luhmann's work include Genomics and Phylogenetic Studies (7 papers), Genome Rearrangement Algorithms (4 papers) and Chromosomal and Genetic Variations (3 papers). Nina Luhmann is often cited by papers focused on Genomics and Phylogenetic Studies (7 papers), Genome Rearrangement Algorithms (4 papers) and Chromosomal and Genetic Variations (3 papers). Nina Luhmann collaborates with scholars based in Canada, Germany and United Kingdom. Nina Luhmann's co-authors include Mark Achtman, João André Carriço, Martin J. Sergeant, Zhemin Zhou, Cátia Vaz, Nabil-Fareed Alikhan, Alexandre P. Francisco, Shijun Sun, Lucy van Dorp and François Balloux and has published in prestigious journals such as Nature Communications, Genome Research and Genome biology.

In The Last Decade

Nina Luhmann

7 papers receiving 799 citations

Hit Papers

GrapeTree: visualization of core genomic relationships am... 2018 2026 2020 2023 2018 2022 200 400 600
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.

  1. GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens
    2018 636 citations Zhemin Zhou, Nabil-Fareed Alikhan et al. Genome Research profile →
  2. Role of mobile genetic elements in the global dissemination of the carbapenem resistance gene blaNDM
    2022 139 citations Mislav Acman, Ruobing Wang et al. Nature Communications profile →

Peers

Nina Luhmann
Stefano Pongolini Italy
Reham M. El‐Tarabili Egypt
Aaron Petkau Canada
Julie Haendiges United States
Richard Goater United Kingdom
Christina A. Ahlstrom United States
Sergio Arredondo-Alonso United Kingdom
Sonya Bodeis‐Jones United States
Matej Medvecký Czechia
Mamuka Kotetishvili United States
Stefano Pongolini Italy
Nina Luhmann
Citations per year, relative to Nina Luhmann Nina Luhmann (= 1×) peers Stefano Pongolini

Countries citing papers authored by Nina Luhmann

Since Specialization
Citations

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

Fields of papers citing papers by Nina Luhmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nina Luhmann

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

All Works

8 of 8 papers shown
1.
Acman, Mislav, Ruobing Wang, Lucy van Dorp, et al.. (2022). Role of mobile genetic elements in the global dissemination of the carbapenem resistance gene blaNDM. Nature Communications. 13(1). 1131–1131. 139 indexed citations breakdown →
2.
Luhmann, Nina, Guillaume Holley, & Mark Achtman. (2021). BlastFrost: fast querying of 100,000s of bacterial genomes in Bifrost graphs. Genome biology. 22(1). 30–30. 14 indexed citations
3.
Zhou, Zhemin, Nabil-Fareed Alikhan, Martin J. Sergeant, et al.. (2018). GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens. Genome Research. 28(9). 1395–1404. 636 indexed citations breakdown →
4.
Luhmann, Nina, Cédric Chauve, Jens Stoye, & Roland Wittler. (2018). Scaffolding of Ancient Contigs and Ancestral Reconstruction in a Phylogenetic Framework. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 15(6). 2094–2100.
5.
Luhmann, Nina, et al.. (2017). Comparative Methods for Reconstructing Ancient Genome Organization. Methods in molecular biology. 1704. 343–362. 8 indexed citations
6.
Luhmann, Nina, et al.. (2017). The SCJ Small Parsimony Problem for Weighted Gene Adjacencies. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 16(4). 1364–1373. 3 indexed citations
7.
Luhmann, Nina, Daniel Doerr, & Cédric Chauve. (2017). Comparative scaffolding and gap filling of ancient bacterial genomes applied to two ancient Yersinia pestis genomes. Microbial Genomics. 3(9). e000123–e000123. 5 indexed citations
8.
Luhmann, Nina, Cédric Chauve, Jens Stoye, & Roland Wittler. (2014). Scaffolding of Ancient Contigs and Ancestral Reconstruction in a Phylogenetic Framework. Lecture notes in computer science. 15(6). 135–143. 4 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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