Matthias Scholz, Ph.D.

Publications

• LC-MS based global metabolite profiling of grapes: solvent extraction protocol optimisation.
  Georgios Theodoridis, Helen Gika, Pietro Franceschi, Lorenzo Caputi, Panagiotis Arapitsas, Matthias Scholz, Domenico Masuero, Ron Wehrens, Urska Vrhovsek and Fulvio Mattivi.
  Metabolomics 2011.
  [ pdf ]
  
  
• Node similarity is the basic principle behind connectivity in complex networks.
  Matthias Scholz.
  arXiv:1010.0803v1 [physics.soc-ph] 2010.
  [ pdf | matlab code ]
  
  
• A computational model of gene expression reveals early transcriptional events at the subtelomeric regions of the malaria parasite, Plasmodium falciparum.
  Matthias Scholz and Martin J. Fraunholz.
  Genome Biology 9:R88, 2008.
  [ pdf | Animation of gene regulation ]
  
  
• Integration of metabolomic and proteomic phenotypes - Analysis of data-covariance dissects starch and RFO metabolism from low and high temperature compensation response in Arabidopsis thaliana.
  Stefanie Wienkoop, Katja Morgenthal, Florian Wolschin, Matthias Scholz, Joachim Selbig, and Wolfram Weckwerth.
  Molecular & Cellular Proteomics, 2008.
  [ pdf ]
  
  
• Nonlinear principal component analysis: neural network models and applications.
  Matthias Scholz, Martin Fraunholz, and Joachim Selbig.
  In Principal Manifolds for Data Visualization and Dimension Reduction, edited by Alexander N. Gorban, Balázs Kégl, Donald C. Wunsch, and Andrei Zinovyev. Volume 58 of LNCSE, pages 44-67. Springer Berlin Heidelberg, 2007.
  [ pdf (all book chapters) | pdf (Springer) | entire book (Springer) | nonlinear PCA toolbox for MATLAB ]
  
  
• Analysing periodic phenomena by circular PCA.
  Matthias Scholz.
  In S. Hochreiter and R. Wagner, editors, Proceedings of the Conference on Bioinformatics Research and Development BIRD'07, LNCS/LNBI Vol. 4414, pages 38-47. Springer-Verlag Berlin Heidelberg, 2007.
  [ pdf (final version at Springer) | pdf (author's pre-version) | bibtex | nonlinear PCA toolbox for MATLAB ]
  
  
• pcaMethods — a bioconductor package providing PCA methods for incomplete data.
  Wolfram Stacklies, Henning Redestig, Matthias Scholz, Dirk Walther, and Joachim Selbig.
  Bioinformatics, 23(9):1164-1167. 2007.
  [ pdf | nonlinear PCA ported to R by Henning Redestig ]
  
  
• Integrated data analysis for genome-wide research.
  Matthias Steinfath, Dirk Repsilber, Matthias Scholz, Dirk Walther and Joachim Selbig.
  In Plant Systems Biology, pages 309-329 edited by Sacha Baginski and Alisdair R. Fernie, Birkhäuser-Verlag, Basel, Boston, Berlin, 2007. (distributed by Springer)
  [ pdf | entire book ]
  
  
• Visualization and analysis of molecular data.
  Matthias Scholz and Joachim Selbig.
  In Wolfram Weckwerth, editor, Metabolomics: methods and protocols. Methods in Molecular Biology Series 358:87-104. Humana Press, New York, 2006.
  [ pdf ]
  
  
• Approaches to analyse and interpret biological profile data.
  Matthias Scholz.
  University of Potsdam, Germany. Ph.D. thesis. 2006.
  URN: urn:nbn:de:kobv:517-opus-7839
  URL: http://opus.kobv.de/ubp/volltexte/2006/783/
  [ pdf (library) | pdf (copy) | bibtex | figures ]
  
  
• Profile data analysis, dimension reduction, clustering and classification.
  Matthias Steinfath, Matthias Scholz, and Joachim Selbig.
  In European Training and Networking Activity. Plant Genomics and Bioinformatics: Expression Micro Arrays and Beyond - a course book. Ljubljana Slovenia, 2005.
  [ pdf | www.eu-summer-school.org ]
  
  
• Non-linear PCA: a missing data approach.
  Matthias Scholz, Fatma Kaplan, Charles L. Guy, Joachim Kopka, and Joachim Selbig.
  Bioinformatics 21(20):3887-3895. 2005.
  [ pdf (final version) | pdf (pre-version in colour) | bibtex ]
  
  
• Correlative GC-TOF-MS-based metabolite profiling and LC-MS-based protein profiling reveal time-related systemic regulation of metabolite-protein networks and improve pattern recognition for multiple biomarker selection.
  Katja Morgenthal, Stefanie Wienkoop, Matthias Scholz, Joachim Selbig, and Wolfram Weckwerth.
  Metabolomics 1(2):109-121. 2005.
  [ pdf ]
  
  
• Independent Component Analysis of Starch Deficient PGM Mutants.
  Matthias Scholz, Yves Gibon, Mark Stitt, and Joachim Selbig.
  In R. Giegerich and J. Stoye, editors, Proceedings of the German Conference on Bioinformatics, pages 95-104. 2004.
  [ pdf ]
  
  
• Metabolite fingerprinting: detecting biological features by independent component analysis.
  Matthias Scholz, Stephan Gatzek, Alistair Sterling, Oliver Fiehn, and Joachim Selbig.
  Bioinformatics 20(15):2447-2454. 2004.
  [ pdf | poster ISMB04 | more about ICA | matlab code | web tool ]
  
  
• Nonlinear PCA based on neural networks.
  Matthias Scholz.
  Dep. of Computer Science, Humboldt-University Berlin. Diploma Thesis. 2002. In German.
  URN: urn:nbn:de:kobv:11-10086728
  [ pdf (library) | pdf (pre-print version)
  
  
• Nonlinear PCA: a new hierarchical approach.
  Matthias Scholz and Ricardo Vigário.
  In M. Verleysen, editor, Proceedings ESANN. 2002.
  [ pdf (pre-print version) | pdf (ESANN) ]
  
  
• Kernel PCA and de-noising in feature spaces.
  Sebastian Mika, Bernhard Schölkopf, Alexander J. Smola, Klaus-Robert Müller, Matthias Scholz, and Gunnar Rätsch.
  In M.S. Kearns, S.A. Solla, and D.A. Cohn, editors, Advances in Neural Information Processing Systems (NIPS) 11, pages 536-542. MIT Press, 1999.
  [ pdf | NIPS:pdf | NIPS:djvu ]
  
  

www.matthias-scholz.de