Daniel Doerr

2.3k citations
24 papers · 280 · h-index 9

Impact in

    • Genome Rearrangement Algorithms
    • Genomics and Phylogenetic Studies
    • Genomics and Chromatin Dynamics
    • Plant biochemistry and biosynthesis
    • Plant Gene Expression Analysis

Papers in

    • Genome Rearrangement Algorithms 14
    • Genetic diversity and population structure 1
    • Genomics and Phylogenetic Studies 11
    • Bioinformatics and Genomic Networks 2
    • Genomics and Chromatin Dynamics 2

Daniel Doerr

23 papers receiving 270 citations

Peers

Daniel Doerr
Comparison fields: 5 of 60
  • Genetics 94
  • Molecular Biology 205
  • Plant Science 106
  • Horticulture 1
  • Food Science 15
Replace Alfred J. Arulandhu with:
Alfred J. Arulandhu Netherlands
Kai Christian Bader Germany
Xiaomei Jiang China
Radha Shivhare India
M. de la Bastide United States
K. James Durbin United States
Likun Long China
Ana C. Wanderley-Nogueira Brazil
Gengmi Li China
Haoyu Chao China
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Citations per field
00.5×
Alfred J. Arulandhu · 1×
Citations per year

Countries citing papers authored by Daniel Doerr

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Doerr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Doerr, 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 Daniel Doerr Line = papers co-authored together Daniel Doerr links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202084
2 201461
3 202116
4 201414
5 201214
6 202313
7 201312
8 201212
9 20249
10 20198
11 20246
12 20175
13 20174
14 20184
15 20204
16 20123
17 20093
18 20163
19 20161
20 20231

About Daniel Doerr

Daniel Doerr is a scholar working on Genetics, Molecular Biology, Plant Science, Paleontology and Social Psychology, having authored 24 papers that have together received 280 indexed citations. Recurring topics across this work include Genome Rearrangement Algorithms (14 papers), Genomics and Phylogenetic Studies (11 papers), Chromosomal and Genetic Variations (7 papers), Bioinformatics and Genomic Networks (2 papers), Genomics and Chromatin Dynamics (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Genetic diversity and population structure (1 paper) and Data-Driven Disease Surveillance (1 paper). The work is most often cited by research in Genetics (94 citations), Molecular Biology (205 citations), Plant Science (106 citations), Horticulture (1 citation) and Food Science (15 citations). Daniel Doerr has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Jens Stoye, Selene L. Fernández-Valverde, Laurence D. Hurst, Peter Fraser, Marco Di Stefano, Eva Wegel, Hans‐Wilhelm Nützmann, Steven Wingett, Anne Osbourn and Marcus Lechner. Their work appears in journals such as Algorithms for Molecular Biology, BMC Genomics, Bioinformatics, Molecular Biology and Evolution and Microbial Genomics.

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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