Daniel Paarmann

15.5k citations
5 papers · 12.8k · 2 hit papers · h-index 5

Impact in

  • Endocrinology top 0.5%
  • Ecology top 0.2%
    • Microbial Community Ecology and Physiology
    • Bacteriophages and microbial interactions

Papers in

    • Diphtheria, Corynebacterium, and Tetanus 1
    • Genomics and Phylogenetic Studies 4
    • Bioinformatics and Genomic Networks 1

Daniel Paarmann

5 papers receiving 12.6k citations

Daniel Paarmann's Hit Papers

The RAST Server: Rapid Annotations using Subsystems Technology 2008 · 9.8k citations
9.8k0+6+12Years since publication2.5k5k7.5k

Peers

Daniel Paarmann
Comparison fields: 5 of 119
  • Endocrinology 728
  • Ecology 3.3k
  • Molecular Medicine 941
  • Pollution 1.1k
  • Microbiology 70
Replace Michael Kubal with:
Michael Kubal United States
Tobias Paczian United States
Elizabeth M. Glass United States
Daniela Bartels Germany
Matthew DeJongh United States
Leslie Klis McNeil United States
Aaron A. Best United States
Olga P. Zagnitko United States
Olga Vassieva United States
Kevin Formsma United States
Daniel Paarmann relative to Michael Kubal United States Michael Kubal's profile →
Citations per field
00.5×1.5×
Michael Kubal · 1×
Citations per year

Countries citing papers authored by Daniel Paarmann

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Paarmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Daniel Paarmann, 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 Paarmann Line = papers co-authored together Daniel Paarmann links everyone, so they are left out of the graph.

All Works

5 of 5 papers shown
#Work
1
The RAST Server: Rapid Annotations using Subsystems Technology
Hit paper breakdown →
20089776
2
The metagenomics RAST server – a public resource for the automatic phylogenetic and functional analysis of metagenomes
Hit paper breakdown →
20082887
3 200685
4 200931
5 200620

About Daniel Paarmann

Daniel Paarmann is a scholar working on Endocrinology, Molecular Biology, Physiology, Genetics and Nuclear Energy and Engineering, having authored 5 papers that have together received 12.8k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (4 papers), Bacterial Genetics and Biotechnology (1 paper), Bioinformatics and Genomic Networks (1 paper), Sympathectomy and Hyperhidrosis Treatments (1 paper) and Diphtheria, Corynebacterium, and Tetanus (1 paper). The work is most often cited by research in Endocrinology (728 citations), Ecology (3.3k citations), Molecular Medicine (941 citations), Pollution (1.1k citations) and Microbiology (70 citations). Daniel Paarmann has collaborated with scholars based in United States and Germany. Frequent co-authors include Folker Meyer, Andreas Wilke, Jan Wilkening, Robert Alan Edwards, Tobias Paczian, Rick L. Stevens, Michael Kubal, Alfred Pühler, Anke Becker and Jörn Kalinowski. Their work appears in journals such as Journal of Biotechnology, BMC Bioinformatics, BMC Genomics and Nucleic Acids Research.

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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