Access the full text.
Sign up today, get DeepDyve free for 14 days.
K. Coombes, Jeffrey Morris, Jianhua Hu, Sarah Edmonson, K. Baggerly (2005)
Serum proteomics profiling—a young technology begins to matureNature Biotechnology, 23
S. Mallat (1998)
A wavelet tour of signal processing
M. Stone (1976)
Cross‐Validatory Choice and Assessment of Statistical PredictionsJournal of the royal statistical society series b-methodological, 36
William Noble (2013)
Support vector machine
B. Scholkopf, K. Tsuda, Jean-Philippe Vert (2005)
Kernel Methods in Computational Biology
B. Mertens, M. Noo, R. Tollenaar, A. Deelder (2006)
Mass Spectrometry Proteomic Diagnosis: Enacting the Double Cross-Validatory ParadigmJournal of computational biology : a journal of computational molecular cell biology, 13 9
D. Ransohoff (2004)
Rules of evidence for cancer molecular-marker discovery and validationNature Reviews Cancer, 4
Alexander Leung, F. Chau, Junbin Gao (1998)
A review on applications of wavelet transform techniques in chemical analysis: 1989–1997Chemometrics and Intelligent Laboratory Systems, 43
Frank-Michael Schleif, M. Lindemann, Mario Diaz, P. Maass, Jens Decker, T. Elssner, Michael Kuhn, H. Thiele (2009)
Support vector classification of proteomic profile spectra based on feature extraction with the bi-orthogonal discrete wavelet transformComputing and Visualization in Science, 12
S. Dudoit, J. Shaffer, Jennifer Boldrick (2003)
Multiple Hypothesis Testing in Microarray ExperimentsStatistical Science, 18
P. Bartlett, J. Shawe-Taylor (1999)
Generalization Performance of Support Vector Machines and Other Pattern Classifiers
William Noble (2004)
Support vector machine applications in computational biology
Kenneth Heilman, Thomas May
For Personal Use. Only Reproduce with Permission from the Lancet Publishing Group
M. Noo, B. Mertens, A. Ozalp, M. Bladergroen, Martijn Werff, C. Velde, A. Deelder, R. Tollenaar (2006)
Detection of colorectal cancer using MALDI-TOF serum protein profiling.European journal of cancer, 42 8
E. Check (2004)
Proteomics and cancer: Running before we can walk?Nature, 429
Motivation: Automatic classification of high-resolution mass spectrometry proteomic data has increasing potential in the early diagnosis of cancer. We propose a new procedure of biomarker discovery in serum protein profiles based on: (i) discrete wavelet transformation of the spectra; (ii) selection of discriminative wavelet coefficients by a statistical test and (iii) building and evaluating a support vector machine classifier by double cross-validation with attention to the generalizability of the results. In addition to the evaluation results (total recognition rate, sensitivity and specificity), the procedure provides the biomarker patterns, i.e. the parts of spectra which discriminate cancer and control individuals. The evaluation was performed on matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) serum protein profiles of 66 colorectal cancer patients and 50 controls.Results: Our procedure provided a high recognition rate (97.3%), sensitivity (98.4%) and specificity (95.8%). The extracted biomarker patterns mostly represent the peaks expressing mean differences between the cancer and control spectra. However, we showed that the discriminative power of a peak is not simply expressed by its mean height and cannot be derived by comparison of the mean spectra. The obtained classifiers have high generalization power as measured by the number of support vectors. This prevents overfitting and contributes to the reproducibility of the results, which is required to find biomarkers differentiating cancer patients from healthy individuals.Availability: The data and scripts used in this study are available at http://www.math.uni-bremen.de/~theodore/MALDIDWT.Contact: theodore@math.uni-bremen.deSupplementary information: Supplementary data are available at Bioinformatics online.
Bioinformatics – Oxford University Press
Published: Jan 6, 2009
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.