Jörg Schaber

3.1k total citations · 1 hit paper
44 papers, 2.3k citations indexed

About

Jörg Schaber is a scholar working on Molecular Biology, Ecology and Nature and Landscape Conservation. According to data from OpenAlex, Jörg Schaber has authored 44 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 8 papers in Ecology and 6 papers in Nature and Landscape Conservation. Recurrent topics in Jörg Schaber's work include Gene Regulatory Network Analysis (13 papers), Fungal and yeast genetics research (12 papers) and Microbial Metabolic Engineering and Bioproduction (10 papers). Jörg Schaber is often cited by papers focused on Gene Regulatory Network Analysis (13 papers), Fungal and yeast genetics research (12 papers) and Microbial Metabolic Engineering and Bioproduction (10 papers). Jörg Schaber collaborates with scholars based in Germany, United States and Sweden. Jörg Schaber's co-authors include Franz‐W. Badeck, Daniel Doktor, Alberte Bondeau, Stephen Sitch, Kristin Böttcher, Wolfgang Lucht, Edda Klipp, Abdul N. Hamood, John Griswold and Nancy L. Carty and has published in prestigious journals such as PLoS ONE, Scientific Reports and New Phytologist.

In The Last Decade

Jörg Schaber

44 papers receiving 2.2k citations

Hit Papers

Responses of spring phenology to climate change 2004 2026 2011 2018 2004 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jörg Schaber Germany 22 838 768 698 447 429 44 2.3k
Lu Sun China 19 852 1.0× 333 0.4× 600 0.9× 110 0.2× 249 0.6× 62 2.2k
John K. Westbrook United States 32 964 1.2× 286 0.4× 1.1k 1.6× 444 1.0× 98 0.2× 89 3.2k
Yan Guo China 29 726 0.9× 151 0.2× 227 0.3× 392 0.9× 198 0.5× 121 2.0k
Francisco Rodríguez Spain 17 888 1.1× 376 0.5× 798 1.1× 105 0.2× 311 0.7× 48 2.9k
Bart Haegeman France 23 419 0.5× 257 0.3× 609 0.9× 235 0.5× 519 1.2× 61 2.0k
Charlotte M. Taylor United States 23 602 0.7× 278 0.4× 280 0.4× 272 0.6× 640 1.5× 138 2.4k
Gunter A. Fischer United States 22 488 0.6× 216 0.3× 219 0.3× 69 0.2× 473 1.1× 64 1.3k
Hsiao‐Hsuan Wang United States 21 99 0.1× 369 0.5× 489 0.7× 295 0.7× 400 0.9× 99 1.5k
Andrés Barbosa Spain 28 227 0.3× 266 0.3× 1.6k 2.3× 176 0.4× 208 0.5× 146 2.8k
Yan Fang China 28 741 0.9× 456 0.6× 239 0.3× 291 0.7× 210 0.5× 142 2.8k

Countries citing papers authored by Jörg Schaber

Since Specialization
Citations

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

Fields of papers citing papers by Jörg Schaber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jörg Schaber

This figure shows the co-authorship network connecting the top 25 collaborators of Jörg Schaber. A scholar is included among the top collaborators of Jörg Schaber 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 Jörg Schaber. Jörg Schaber 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.
Lasch‐Born, Petra, Felicitas Suckow, Christopher Reyer, et al.. (2020). Description and evaluation of the process-based forest model 4C v2.2 at four European forest sites. Geoscientific model development. 13(11). 5311–5343. 16 indexed citations
2.
Figueiredo, Ana Sofia, Theresa Kouril, Dominik Esser, et al.. (2017). Systems biology of the modified branched Entner-Doudoroff pathway in Sulfolobus solfataricus. PLoS ONE. 12(7). e0180331–e0180331. 10 indexed citations
3.
Schaber, Jörg, et al.. (2016). The role of time delay in adaptive cellular negative feedback systems. Journal of Theoretical Biology. 398. 64–73. 5 indexed citations
4.
Schaber, Jörg, et al.. (2016). Simulation of forest tree species’ bud burst dates for different climate scenarios: chilling requirements and photo-period may limit bud burst advancement. International Journal of Biometeorology. 60(11). 1711–1726. 14 indexed citations
5.
Andersson, Mikael, et al.. (2016). Systems Level Analysis of the Yeast Osmo-Stat. Scientific Reports. 6(1). 17 indexed citations
6.
Schaber, Jörg, et al.. (2015). Development of a robust DNA damage model including persistent telomere-associated damage with application to secondary cancer risk assessment. Scientific Reports. 5(1). 13540–13540. 8 indexed citations
7.
Studencka‐Turski, Maja, et al.. (2015). FoCo: a simple and robust quantification algorithm of nuclear foci. BMC Bioinformatics. 16(1). 392–392. 38 indexed citations
8.
Jacobson, Therese, Vijay Garla, Clara Navarrete, et al.. (2014). Mathematical modelling of arsenic transport, distribution and detoxification processes in yeast. Molecular Microbiology. 92(6). 1343–1356. 15 indexed citations
9.
Nordlander, Bodil, Kuk-Ki Hong, Therese Jacobson, et al.. (2013). Quantitative Analysis of Glycerol Accumulation, Glycolysis and Growth under Hyper Osmotic Stress. PLoS Computational Biology. 9(6). e1003084–e1003084. 87 indexed citations
10.
Badeck, Franz‐W., et al.. (2013). The plant phenological online database (PPODB): an online database for long-term phenological data. International Journal of Biometeorology. 57(5). 805–812. 11 indexed citations
11.
Schaber, Jörg. (2012). Easy parameter identifiability analysis with COPASI. Biosystems. 110(3). 183–185. 22 indexed citations
13.
Schaber, Jörg & Edda Klipp. (2010). Model-based inference of biochemical parameters and dynamic properties of microbial signal transduction networks. Current Opinion in Biotechnology. 22(1). 109–116. 28 indexed citations
14.
Schaber, Jörg, Emma Eriksson, Serge Pelet, et al.. (2010). Biophysical properties of Saccharomyces cerevisiae and their relationship with HOG pathway activation. European Biophysics Journal. 39(11). 1547–1556. 121 indexed citations
15.
Schaber, Jörg, Wolfram Liebermeister, & Edda Klipp. (2009). Nested uncertainties in biochemical models. IET Systems Biology. 3(1). 1–9. 25 indexed citations
16.
Delmotte, François, Claude Rispe, Jörg Schaber, Francisco J. Silva, & Andrés Moyá. (2006). Tempo and mode of early gene loss in endosymbiotic bacteria from insects.. BMC Evolutionary Biology. 6(1). 56–56. 23 indexed citations
17.
Schaber, Jörg, Bente Kofahl, Axel Kowald, & Edda Klipp. (2006). A modelling approach to quantify dynamic crosstalk between the pheromone and the starvation pathway in baker's yeast. FEBS Journal. 273(15). 3520–3533. 29 indexed citations
18.
Doktor, Daniel, et al.. (2005). Using satellite imagery and ground observations to quantify the effect of intra-annually changing temperature patterns on spring time phenology. publish.UP (University of Potsdam). 2005. 4 indexed citations
19.
Schaber, Jörg, Claude Rispe, Jennifer J. Wernegreen, et al.. (2005). Gene expression levels influence amino acid usage and evolutionary rates in endosymbiotic bacteria. Gene. 352. 109–117. 23 indexed citations
20.
Schaber, Jörg & Franz‐W. Badeck. (2003). Physiology-based phenology models for forest tree species in Germany. International Journal of Biometeorology. 47(4). 193–201. 163 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026