Edda Klipp

10.9k citations
169 papers · 5.8k · h-index 39

Impact in

  • Aging top 2%
    • Gene Regulatory Network Analysis
    • Microbial Metabolic Engineering and Bioproduction
    • Bioinformatics and Genomic Networks
    • Fungal and yeast genetics research
    • Protein Structure and Dynamics
    • Single-cell and spatial transcriptomics

Papers in

    • Gene Regulatory Network Analysis 75
    • Microbial Metabolic Engineering and Bioproduction 59
    • Fungal and yeast genetics research 57
    • Bioinformatics and Genomic Networks 31
    • Protein Structure and Dynamics 12
    • DNA Repair Mechanisms 6
    • Microtubule and mitosis dynamics 7

Edda Klipp

164 papers receiving 5.7k citations

Peers

Edda Klipp
Comparison fields: 5 of 166
  • Aging 149
  • Molecular Biology 4.4k
  • Biophysics 189
  • Cell Biology 400
  • Modeling and Simulation 94
Replace Gábor Balázsi with:
Gábor Balázsi United States
Diego di Bernardo Italy
Wenzhe Ma China
Jana Wolf Germany
Roger Brent United States
Johannes Schuchhardt Germany
Tamás Korcsmáros United Kingdom
Chikara Furusawa Japan
Rune Linding United Kingdom
Jacky L. Snoep Netherlands
Edda Klipp relative to Gábor Balázsi United States Gábor Balázsi's profile →
Citations per field
00.5×2×2.6×
Gábor Balázsi · 1×
Citations per year

Countries citing papers authored by Edda Klipp

Since Specialization
Citations

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

Fields of papers citing papers by Edda Klipp

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 169 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005449
2 2005351
3 2005300
4 2010257
5 2017180
6 2006169
7 2015162
8 2010128
9 2006124
10 2008123
11 2004100
12 201096
13 201394
14 200291
15 200790
16 201189
17 201286
18 201381
19 201178
20 199773

About Edda Klipp

Edda Klipp is a scholar working on Molecular Biology, Cell Biology, Computational Theory and Mathematics, Plant Science and Genetics, having authored 169 papers that have together received 5.8k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (75 papers), Microbial Metabolic Engineering and Bioproduction (59 papers), Fungal and yeast genetics research (57 papers), Bioinformatics and Genomic Networks (31 papers), Protein Structure and Dynamics (12 papers), Computational Drug Discovery Methods (8 papers), Microtubule and mitosis dynamics (7 papers) and DNA Repair Mechanisms (6 papers). The work is most often cited by research in Aging (149 citations), Molecular Biology (4.4k citations), Biophysics (189 citations), Cell Biology (400 citations) and Modeling and Simulation (94 citations). Edda Klipp has collaborated with scholars based in Germany, United States and Sweden. Frequent co-authors include Wolfram Liebermeister, Stefan Hohmann, Axel Kowald, Zhike Zi, Bodil Nordlander, Reinhart Heinrich, Jörg Schaber, Hans Lehrach, Peter Gennemark and Christoph Wierling. Their work appears in journals such as Bioinformatics, PLoS Computational Biology, PLoS ONE, Molecular Systems Biology and BMC Bioinformatics.

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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