Peer reviewed international journals


Kollarovic G, Studencka M, Ivanova L, Lauenstein C, Heinze K, Lapytsko A, Rastgou Talemi S, Figueiredo A, Schaber J (2016) To senesce or not to senesce: how primary human fibroblasts decide
their cell fate after DNA damage. Aging (Albany NY) 8.1 <PubMed> <pdf>


Lapytsko A, Kollarovic G, Schaber J (2015) FoCo: a simple and robust quantification algorithm of nuclear foci. accepted. BMC Bioinformatics 16. <online> <pdf> <FoCo auf sourceforge >

Rastgou Talemi S, Kollarovic G, Lapytsko A, Schaber J (2015) Development of a robust DNA damage model including persistent telomere-associated damage with application to secondary cancer risk assessment. Scientific Reports 5, Article number: 13540 (2015) doi:10.1038/srep13540 <online> <pdf>


Rastgou Talemi S, Jacobson T, Garla V, Navarrete C, Wagner A, Tamás MJ, Schaber J (2014) Mathematical modeling of arsenic transport, distribution and detoxification processes in yeast. Mol. Microbiol. 92(6), 1343–1356: <online> <pdf>

Schaber J, Lapytkso A, Flockerzi D (2014) Nested autoinhibitory feedbacks alter the resistance of homeostatic adaptive biochemical networks. J. R. Soc. Interface 11:20130971 <online> <pdf> <Supplementary> .


Petelenz-Kurdziel E, Kuehn C, Nordlander B, Klein D, Hong K, Jacobson T, Dahl P, Schaber J, Nielsen J, Hohmann S, Klipp E (2013) Quantitative Analysis of Glycerol Accumulation, Glycolysis and Growth under Hyper Osmotic Stress. PloS Comp. Biol. 9(6) <online> <pdf>

Dierenbach J, Badeck F-W., Schaber J. (2013) The plant phenological online database (PPODB): an online database for long-term phenological data. Int. J. Biomet. 57(5):805-12 <online> <pdf>


Schaber J, Baltanas R, Bush A, Klipp E, Colman-Lerner A (2012) Modelling reveals novel roles of two parallel signalling pathways and homeostatic feedbacks in yeast. Mol. Syst. Biol 8:622. <online> <pdf> <Supplementary>

Schaber J (2012) Easy parameter identifiability with COPASI. BioSystems 110(3):183–185 <online> <pdf> <Supplementary>


Adrover MÀ, Zi Z, Duch A, Schaber J, González-Novo A, Jimenez J, Nadal-Ribelles M, Clotet J, Klipp E, Posas F (2011) Multi-component control of the G1-S network by the SAPK Hog1 upon osmostress. Science Signaling 4(192) <PubMed> <pdf>

Schaber J., Flöttmann M., Li J., Tiger C-F., Hohmann S, Klipp E. (2011) Automated ensemble modeling with modelMaGe: analyzing feedback mechanisms in the Sho1 branch of the HOG pathway. PLoS ONE 6(3): e14791. doi:10.1371/journal.pone.0014791. <PubMed> <pdf> <Supplementary> <The Master Model> <Candidate Models Generation Directives> <The Data>

Schaber J., Klipp E. (2011) Model-based inference of biochemical parameters and dynamic properties of microbial signal transduction networks. Current Opinion in Biotechnology 22:109-116. <PubMed> <pdf>


Schaber J. et al. (2010) Biophysical properties of Saccharomyces cerevisiae and their relationship with HOG pathway activation. Eur Biophys J. 39(11):1547ff <PubMed> <pdf> <Supplementary>


Schaber J., Liebermeister W., Klipp E. (2009) Nested uncertainty in biochemical models. IET Systems Biology 3:1-9. <PubMed> <pdf>


Kühn C., Petelenz E., Nordlander B., Schaber J., Hohmann S., Klipp E. (2008) Exploring the impact of osmoadaptation on glycolysis using time-varying response-coefficients. Genome Informatics 20. <PubMed> <pdf> <Supplementary Material>

Flöttmann M., Schaber J., Hoops S., Klipp E., Mendes P. (2008) ModelMage: A Tool for Automatic Model Generation, Selection and Management. Genome Informatics 20. <PubMed> <pdf>


Klipp E., Liebermeister W., Helbig A., Kowald A., Schaber J. (2007) Systems biology standards–the community speaks. Nat Biotechnol 25(4):390-1 <PubMed> <pdf>


Delmotte F., Rispe C., Schaber J., Silva FJ., Moya A. (2006) Tempo and mode of early gene loss in endosymbiotic bacteria from insects. BMC Evol. Biol 6:56 <PubMed> <pdf>

Schaber J., Kofahl B., Kowald A., Klipp E. (2006) A modelling approach to quantify dynamic crosstalk between the pheromone and the starvation pathway in baker’s yeast. FEBS Journal 273:3520-3533. <PubMed> <pdf> <Supplementary Material>

Badeck F.-W., Doktor D., Bondeau A., Koslowsky D., Schaber J. (2006) Complementary Views on Spring Phenology derived from Satellite and Ground Observations. Geophysical Research Abstracts Vol. 8. <pdf>


Schaber J. et al. (2005) Putative gene expression levels influence amino acid usage and evolutionary rates in endosymbiontic bacteria. Gene 352:109-117. <PubMed> <pdf>

Schaber J., F.-W. Badeck (2005). Plant phenology in Germany in the 20th century. Regional Environmental Change 5:37-46. <springerlink> <pdf>


Badeck F.-W., A. Bondeau, K. Bottcher, D. Doktor, W. Lucht, J. Schaber, S. Sitch (2004) Responses of spring phenology to Climate Change. The New Phytologist 162(2):295-309.


Schaber J., F.-W. Badeck (2003) Physiology-based phenology models for forest tree species in Germany. Int J
Biometeorol. 47(4): 193-201. <PubMed> <pdf>


Schaber J., F.-W. Badeck (2002) Evaluation of methods for the combination of phenological time series and outlier detection. Tree Physiol. 22:973-982. <PubMed> <pdf>


David T. Price, Niklaus E. Zimmermann, Peter J. van der Meer, Manfred J. Lexer, Paul Leadley, Irma T. M. Jorritsma, Jörg Schaber, Donald F. Clark, Petra Lasch, Steve McNulty, Jianguo Wu, Benjamin Smith (2001) Regeneration in Gap Models: Priority Issues for Studying Forest Responses to Climate Change.Climatic Change 51:475-508. <springerlink>

Badeck, F.-W., Lischke, H., Bugmann, H., Hickler, T.,Hönninger, K., Lasch, P., Lexer, M.J., Mouillot, F., Schaber, J. and Smith, B. (2001) Tree species composition in European pristine forests. Comparison of stand data to model predictions.Climatic Change 51:307-347. <springerlink>

Book chapters, conference proceedings, etc.


Schaber, J., Badeck F.-W., Doktor D., Bloh W. (2010) Combining messy phenological time series. In ‘Phenological Research – Methods for Environmental and Climate Change Analysis. Irene L. Hudson and Marie R. Keatley (Eds.), Springer-Verlag, DOI: 10.1007/978-90-481-3335-2_7. p. 147-158′ <pdf>


Schaber, J., Klipp E. (2008) Short-term volume and turgor regulation in yeast. Essays in Biochemisty 45:149-160 <pdf> <pubmed>

Klipp E., Schaber J. (2008) Modelling the dynamics of Stress Activated Protein Kinases (SAPK) in cellular stress response. In ‚Stress-activated Protein Kinases‘. Posas and Nebrada (Eds.). Topics in Current Genetics. Springer.


Klipp E., Schaber J. (2006) Modeling of Signal Transduction in Yeast – Sensitivity and Model Analysis. In ‚Understanding and Exploiting Systems Biology in Biomedicine and Bioprocesses‘. Fundación CajaMurcia, Mucia, Spain. p. 15-30. <pdf>


Doktor D., F. W. Badeck, F. Hattermann, J. Schaber, M. McAllister (2005) Analysis and modelling of spatially and temporally varying phenological phases, in: Geostatistics for Environmental Applications. Proceedings of the Fifth European Conference on Geostatistics for Environmental Applications. Editors: Philippe Renard, Helene Demougeot-Renard, Roland Froidevaux. p. 137-148. Springer <pdf>


Schaber J. (2002). Die Phänologische Pflanzenentwicklung in Deutschland im 20. Jahrhundert. Phänologie Journal des Deutschen Wetterdienstes 19:4-5.


Suckow, F., Badeck, F-W., Lasch, P., Schaber, J. (2001) Nutzung von Level-II-Beobachtungen für Test und Anwendungen des Sukzessionsmodells FORESEE. Beitr. Forstwirtsch. u. Landschaftsökol. 35:84-87


Schaber J., F. Badeck, P. Lasch (1998) Ein Modell der Sukzessionsdynamik europäischer Wälder. Beiträge zum Herbstkolloqium der AG Ökologie der Internationalen Biometrischen Gesellschaft – Deutsche Region. Freiburg 30.9.-2.10.1998/ herausgegeben von D.R. Pelz, O.Rau, J. Saborowski. Ljubljana: Biotechnische Fakultät, Abteilung für Forstwirtschaft, 1999. – (die grüne Reihe)

Theses and software

ModelMaGe: Model Management and Generations. project page.

Schaber J. (2003) pheno: Auxiliary functions for phenological data analysis. R package.

Schaber J. (2002) Phenology in Germany in the 20th century : methods, analyses and models. PhD Thesis, University of Potsdam. <pdf>

Schaber J. (1997) FARMSIM: A dynamic model for the simulation of yields, nutrient cycling and resource flows on Philippine small-scale farming systems. Master thesis. Applied Systems Science. University of Osnabrück.

This thesis can be downloaded in different formats: The thesis as gzip-packed postscript file (600 K —> 6.820 K) The thesis as pkzip-packed postscript file (563 K —> 6.820 K) The thesis as pkzip-packed WinWord 6.0 file (547 K —> 3.604 K) pkzip-packed STELLA II Farm Simulation Model (86 K —> 343 K)