Oliver Eulenstein

2.2k total citations
69 papers, 1.0k citations indexed

About

Oliver Eulenstein is a scholar working on Molecular Biology, Genetics and Plant Science. According to data from OpenAlex, Oliver Eulenstein has authored 69 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Molecular Biology, 44 papers in Genetics and 13 papers in Plant Science. Recurrent topics in Oliver Eulenstein's work include Genomics and Phylogenetic Studies (60 papers), Genetic diversity and population structure (38 papers) and Bioinformatics and Genomic Networks (15 papers). Oliver Eulenstein is often cited by papers focused on Genomics and Phylogenetic Studies (60 papers), Genetic diversity and population structure (38 papers) and Bioinformatics and Genomic Networks (15 papers). Oliver Eulenstein collaborates with scholars based in United States, Poland and Germany. Oliver Eulenstein's co-authors include J. Gordon Burleigh, Mukul S. Bansal, David Fernández‐Baca, André Wehe, Paweł Górecki, Martin Vingron, Ruchi Chaudhary, Alexey Markin, Michael J. Sanderson and Todd Vision and has published in prestigious journals such as Bioinformatics, BMC Bioinformatics and Systematic Biology.

In The Last Decade

Oliver Eulenstein

60 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Oliver Eulenstein United States 19 876 594 215 160 118 69 1.0k
Mukul S. Bansal United States 16 818 0.9× 472 0.8× 270 1.3× 138 0.9× 72 0.6× 47 987
Cuong Than United States 8 626 0.7× 551 0.9× 191 0.9× 214 1.3× 115 1.0× 14 844
Vincent Berry France 19 665 0.8× 464 0.8× 244 1.1× 246 1.5× 151 1.3× 46 1.1k
Serita M. Nelesen United States 7 437 0.5× 229 0.4× 173 0.8× 114 0.7× 87 0.7× 10 758
Glenn Hickey United States 14 656 0.7× 399 0.7× 348 1.6× 77 0.5× 103 0.9× 28 1.0k
Francesc Rosselló Spain 15 553 0.6× 303 0.5× 278 1.3× 165 1.0× 202 1.7× 67 1.0k
Katharina T. Huber United Kingdom 20 858 1.0× 668 1.1× 320 1.5× 369 2.3× 212 1.8× 93 1.5k
Lars Arvestad Sweden 21 1.0k 1.2× 495 0.8× 529 2.5× 132 0.8× 64 0.5× 39 1.4k
M. Shel Swenson United States 8 716 0.8× 526 0.9× 238 1.1× 332 2.1× 157 1.3× 8 1.1k
Sagi Snir Israel 21 1.0k 1.2× 614 1.0× 176 0.8× 108 0.7× 155 1.3× 83 1.4k

Countries citing papers authored by Oliver Eulenstein

Since Specialization
Citations

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

Fields of papers citing papers by Oliver Eulenstein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Oliver Eulenstein

This figure shows the co-authorship network connecting the top 25 collaborators of Oliver Eulenstein. A scholar is included among the top collaborators of Oliver Eulenstein 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 Oliver Eulenstein. Oliver Eulenstein 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.
Banerjee, Priyanka, Oliver Eulenstein, & Iddo Friedberg. (2024). Discovering genomic islands in unannotated bacterial genomes using sequence embedding. Bioinformatics Advances. 4(1). vbae089–vbae089. 5 indexed citations
2.
Markin, Alexey, et al.. (2024). Asymmetric Cluster-Based Measures for Comparative Phylogenetics. Journal of Computational Biology. 31(4). 312–327.
3.
Markin, Alexey, et al.. (2023). PARNAS: Objectively Selecting the Most Representative Taxa on a Phylogeny. Systematic Biology. 72(5). 1052–1063. 20 indexed citations
4.
Markin, Alexey, et al.. (2023). Phylogenetic diversity statistics for all clades in a phylogeny. Bioinformatics. 39(Supplement_1). i177–i184. 1 indexed citations
5.
Markin, Alexey, et al.. (2022). RF-Net 2: fast inference of virus reassortment and hybridization networks. Bioinformatics. 38(8). 2144–2152. 7 indexed citations
6.
Markin, Alexey & Oliver Eulenstein. (2021). Quartet-based inference is statistically consistent under the unified duplication-loss-coalescence model. Bioinformatics. 37(22). 4064–4074. 15 indexed citations
7.
Nguyen, Huy, Ashish Jain, Oliver Eulenstein, & Iddo Friedberg. (2019). Tracing the ancestry of operons in bacteria. Bioinformatics. 35(17). 2998–3004. 8 indexed citations
8.
Markin, Alexey & Oliver Eulenstein. (2016). Manhattan Path-Difference Median Trees. 404–413. 1 indexed citations
9.
Górecki, Paweł, et al.. (2013). Exact Solutions for Classical Gene Tree Parsimony Problems. International Conference on Bioinformatics. 1 indexed citations
10.
Górecki, Paweł & Oliver Eulenstein. (2013). DrML: Probabilistic Modeling of Gene Duplications. Journal of Computational Biology. 21(1). 89–98. 5 indexed citations
11.
Górecki, Paweł, Oliver Eulenstein, & Jerzy Tiuryn. (2013). Unrooted Tree Reconciliation: A Unified Approach. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 10(2). 522–536. 25 indexed citations
12.
Krause, Roland, et al.. (2012). Exploring biological interaction networks with tailored weighted quasi-bicliques. BMC Bioinformatics. 13(S10). S16–S16. 11 indexed citations
13.
Górecki, Paweł, et al.. (2012). GTP Supertrees from Unrooted Gene Trees: Linear Time Algorithms for NNI Based Local Searches. Lecture notes in computer science. 7292. 102–114. 2 indexed citations
14.
Chaudhary, Ruchi, J. Gordon Burleigh, & Oliver Eulenstein. (2012). Efficient error correction algorithms for gene tree reconciliation based on duplication, duplication and loss, and deep coalescence. BMC Bioinformatics. 13(S10). S11–S11. 14 indexed citations
15.
Bansal, Mukul S., J. Gordon Burleigh, & Oliver Eulenstein. (2010). Efficient genome-scale phylogenetic analysis under the duplication-loss and deep coalescence cost models. BMC Bioinformatics. 11(S1). S42–S42. 45 indexed citations
16.
Chaudhary, Ruchi, Mukul S. Bansal, André Wehe, David Fernández‐Baca, & Oliver Eulenstein. (2010). iGTP: A software package for large-scale gene tree parsimony analysis. BMC Bioinformatics. 11(1). 574–574. 62 indexed citations
17.
Eulenstein, Oliver, et al.. (2006). Reconciling Gene Trees with Apparent Polytomies. Iowa State University Digital Repository (Iowa State University).
18.
Eulenstein, Oliver, et al.. (2006). Minimum-Flip Supertrees: Complexity and Algorithms. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 3(2). 165–173. 23 indexed citations
19.
Yuan, Yan P., Oliver Eulenstein, Martin Vingron, & Peer Bork. (1998). Towards detection of orthologues in sequence databases.. Bioinformatics. 14(3). 285–289. 56 indexed citations
20.
Eulenstein, Oliver, Boris Mirkin, & Martin Vingron. (1998). Duplication-Based Measures of Difference Between Gene and Species Trees. Journal of Computational Biology. 5(1). 135–148. 30 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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