Supplemental Material
Diese Seite enthält das Supplemental Material für die unten aufgeführten Publikationen.
Katrin Madjar and Jörg Rahnenführer:
Weighted Cox regression for the prediction of heterogeneous patient subgroups
BMC Medical Informatics and Decision Making, 2021
A file containing data and R code can be downloaded [here].
Vera Rieder, Karin U. Schork, Laura Kerschke, Bernhard Blank-Landeshammer, Albert Sickmann and Jörg Rahnenführer:
Comparison and evaluation of clustering algorithms for tandem mass spectra
J. Proteome Res., 2017
A file containing R code of clustering algorithms and measures for assessment of the quality of cluster algorithms can be downloaded [here].
Our R guide related to the manuscript can be downloaded [here].
Vera Rieder, Bernhard Blank-Landeshammer, Marleen Stuhr, Tilman Schell, Karsten Biß, Laxmikanth Kollipara, Achim Meyer, Markus Pfenninger, Hildegard Westphal, Albert Sickmann and Jörg Rahnenführer:
DISMS2: A flexible algorithm for direct proteome-wide distance calculation of LC-MS/MS runs
BMC Bioinformatics, 2017
A file containing R code of DISMS2 can be downloaded [here].
Miriam Lohr, Birte Hellwig, Karolina Edlund, Johanna Mattsson, Johan Botling, Marcus Schmidt, Jan G. Hengstler, Patrick Micke, Jörg Rahnenführer:
Identification of sample annotation errors in gene expression datasets
Archives of Toxicology, 2015
A file containing the description of the algorithms used for building and applying the sex classifier can be found [here].
It contains the following three algorithms:
1. Algorithm for selection of suitable variables (genes, probe sets) for sex classification
2. Algorithm for normalization of datasets
3. Algorithm for the sex classifier
A file containing some additional tables can be found [here].
A file containing some additional figures can be found [here].
Marco Grzegorczyk, Dirk Husmeier:
Improvements in the reconstruction of time-varying gene regulatory networks: dynamic programming and regularization by information sharing among genes
Bioinformatics, 2011
Our Matlab implementation of the regularized cpBGe model can be downloaded [here].
A description and a worked example is available [here].
Marco Grzegorczyk, Dirk Husmeier and Jörg Rahnenführer:
Modelling non-stationary dynamic gene regulatory processes with the BGM model
Computational Statistics, 2011
A zip folder containing our Matlab implementation of the RJMCMC algorithm can be downloaded [here].
A supplementary paper providing details, which for space restrictions could not be included in the main paper, can be downloaded [here] .
Kai Kammers, Michel Lang, Jan G. Hengstler, Marcus Schmidt and Jörg Rahnenführer:
Survival models with preclustered gene groups as covariates
BMC Bioinformatics, 2011
A file containing R code for model selection and evaluation can be downloaded [here].
Birte Hellwig, Jan G. Hengstler, Marcus Schmidt, Mathias C. Gehrmann, Wiebke Schormann, Jörg Rahnenführer:
Comparison of scores for bimodality of gene expression distributions and genome-wide evaluation of the prognostic relevance of high-scoring genes
BMC Bioinformatics, 2010
A file containing R code for computing measures of bimodality and linking them to survival data can be downloaded [here].
Katharina Podwojski, Arno Fritsch, Daniel C. Chamrad, Wolfgang Paul, Barbara Sitek, Kai Stühler, Petra Mutzel, Christian Stephan, Helmut E. Meyer, Wolfgang Urfer, Katja Ickstadt, Jörg Rahnenführer:
Retention Time Alignment Algorithms for LC/MS Data must consider Nonlinear Shifts
Bioinformatics, 2009
A text file containing the R code for the regression-based alignment algorithms can be downloaded [here].
Please read the file [readme] for instructions on the usage of the R code.
The simulated data sets analyzed in the paper can be downloaded here: [Data10ppm] and [Data100ppm]