Papers citing MedicWave software

[1]
Jorg Hanrieder, Anna Karlsson, Maria Falth, Sofie Eriksson-Mammo, Jonas Bergquist and Malin Andersson.
L-DOPA-induced dyskinesia is associated with regional increase of striatal dynorphin peptides as elucidated by imaging mass spectrometry.
Mol Cell Proteomics. 2011 Jul 6.

[2]
Erik Portelius, Robert A. Dean, Mikael K. Gustavsson, Ulf Andreasson, Henrik Zetterberg, Eric Siemers, Kaj Blennow.
A novel Aβ isoform pattern in CSF reflects γ-secretase inhibition in Alzheimer disease.
Alzheimers Res Ther. 2010 Mar 29;2(2):7.

 

References to methods used in our software

[1]
Oliver Kohlbacher and Knut Reinert.
OpenMS and TOPP: Open source software for LC-MS data analysis.
In Simon J. Hubbard and Andrew R. Jones, editors, Proteome
Bioinformatics, volume 604, chapter 14. Humana Press. Methods in Molecular Biology, 2010.

[2]
Kurt Varmuza and Peter Filzmoser.
Introduction to Multivariate Statistical Analysis in Chemometrics.
Taylor & Francis - CRC Press, Boca Raton, FL, 2009.

[3]
Trevor Hastie, Robert Tibshirani, and J. H. Friedman.
The elements of statistical learning: data mining, inference, and prediction.
New York: Springer-Verlag, 2008.

[4]
Marc Sturm, Andreas Bertsch, Clemens Gröpl, Andreas Hildebrandt, Rene Hussong,
Eva Lange, Nico Pfeifer, Ole Schulz-Trieglaff, Alexandra Zerck, Knut Reinert,
and Oliver Kohlbacher.
OpenMS - an open-source software framework for mass spectrometry.
BMC Bioinformatics, 9(163), 2008.

[5]
Diana Chan, Susan Bridges, and Shane Burgess.
An ensemble method for identifying robust features for biomarker discovery.
In Huan Liu and Hiroshi Motoda, editors, Computational Methods of Feature Selection, chapter 19, pages 377–392. CRC Press, 2007.

[6]
Guojun Gan, Chaoqun Ma, and Jianhong Wu.
Data Clustering: Theory, Algorithms, and Applications, volume 20.
Society for Industrial and Applied Mathematics, 2007.

[7]
M. Hauskrecht, R. Pelikan, M. Valko, and J. Lyons-Weiler.
Feature selection and dimensionality reduction in genomics and proteomics.
In W. Dubitzky, M. Granzow, and D.P. Berrar, editors, Fundamentals of Data Mining in Genomics and Proteomics, chapter 7, pages 149–172. Springer, 2007.

[8]
Eva Lange, Clemens Gröpl, Ole Schulz-Trieglaff, Andreas Leinenbach, Christian
Huber, and Knut Reinert.
A geometric approach for the alignment of liquid chromatography—mass spectrometry data.
Bioinformatics, 23(13):i273–i281, 2007.

[9]
Yvan Saeys, Iñaki Inza, and Pedro Larrañaga.
A review of feature selection techniques in bioinformatics.
Bioinformatics, 23(19):2507–2517, 2007.

[10]
Werner Dubitzky, Martin Granzow, and Daniel P. Berrar.
Fundamentals of Data Mining in Genomics and Proteomics.
Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2006.

[11]
Eva Lange, Clemens Gropl, Knut Reinert, Oliver Kohlbacher, and Andreas Hildebrandt.
High accuracy peak-picking of proteomics data using wavelet techniques.
In Pacific Symposium on Biocomputing 2006. Maui, pages 243–254, 2006.

[12]
Polina Golland, Feng Liang, Sayan Mukherjee, and Dmitry Panchenko.
Permutation tests for classification.
In Peter Auer and Ron Meir, editors, Learning Theory, volume 3559 of Lecture Notes in Computer Science, pages 501–515. Springer, 2005.

[13]
D.V. Nguyen and D.M. Rocke.
Tumor classification by partial least squares using microarray gene expression data.
Bioinformatics, 18(1):39–50, 2002.