The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments
Open accessAbstract
Motivation: There has been much interest in using patterns derived from surface-enhanced laser desorption and ionization (SELDI) protein mass spectra from serum to differentiate samples from patients both with and without disease. Such patterns have been used without identification of the underlying proteins responsible. However, there are questions as to the stability of this procedure over multiple experiments. Results: We compared SELDI proteomic spectra from serum from three experiments by the same group on separating ovarian cancer from normal tissue. These spectra are available on the web at http://clinicalproteomics.steem.com. In general, the results were not reproducible across experiments. Baseline correction prevents reproduction of the results for two of the experiments. In one experiment, there is evidence of a major shift in protocol mid-experiment which could bias the results. In another, structure in the noise regions of the spectra allows us to distinguish normal from cancer, suggesting that the normals and cancers were processed differently. Sets of features found to discriminate well in one experiment do not generalize to other experiments. Finally, the mass calibration in all three experiments appears suspect. Taken together, these and other concerns suggest that much of the structure uncovered in these experiments could be due to artifacts of sample processing, not to the underlying biology of cancer. We provide some guidelines for design and analysis in experiments like these to ensure better reproducible, biologically meaningfully results. Availability: The MATLAB and Perl code used in our analyses is available at http://bioinformatics.mdanderson.org
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Genetic algorithms in search, optimization, and machine learning
(1989) · Choice Reviews Online · doi:10.5860/choice.27-0936 · Cited by 49,010
Holland, J. H. (1992) · The MIT Press eBooks · doi:10.7551/mitpress/1090.001.0001 · Cited by 47,002
Genetic Algorithms in Search, Optimization and Machine Learning
Goldberg, D. E., & Robson, D. (1988) · Cited by 18,391
Goldberg, D. E., & Shakespeare, W. (2002) · Cited by 16,088
Use of proteomic patterns in serum to identify ovarian cancer
Petricoin, E. F., Ardekani, A. M., Hitt, B. A., Levine, P. J., Fusaro, V. A., Steinberg, S. M., Mills, G. B., Simone, C., Fishman, D. A., Kohn, E. C., et al. (2002) · The Lancet · doi:10.1016/s0140-6736(02)07746-2 · Cited by 3,236
Mass spectrometry: principles and applications
(1997) · Choice Reviews Online · doi:10.5860/choice.35-1527 · Cited by 758
Adam, B.-L., Qu, Y., Davis, J. W., Ward, M. D., Clements, M. A., Cazares, L. H., Semmes, O. J., Schellhammer, P. F., Yasui, Y., Feng, Z., et al. (2002) · PubMed · Cited by 612
A data review and re-assessment of ovarian cancer serum proteomic profiling
Sorace, J. M., & Zhan, M. (2003) · BMC Bioinformatics · doi:10.1186/1471-2105-4-24 · Cited by 336
ProteinChip clinical proteomics: computational challenges and solutions.
Fung, E. T., & Enderwick, C. (2002) · PubMed · Cited by 132
Cited by
Zhang, Z., Bast, R. C., Yu, Y., Li, J., Sokoll, L. J., Rai, A. J., Rosenzweig, J. M., Cameron, B., Wang, Y. Y., Meng, X.-Y., et al. (2004) · Cancer Research · doi:10.1158/0008-5472.can-04-0746 · Cited by 934
Revisiting biomarker discovery by plasma proteomics
Geyer, P. E., Holdt, L. M., Teupser, D., & Mann, M. (2017) · Molecular Systems Biology · doi:10.15252/msb.20156297 · Cited by 917
Henry, N. L., & Hayes, D. F. (2012) · Molecular Oncology · doi:10.1016/j.molonc.2012.01.010 · Cited by 849
Statistical strategies for avoiding false discoveries in metabolomics and related experiments
Broadhurst, D. I., & Kell, D. B. (2007) · Metabolomics · doi:10.1007/s11306-006-0037-z · Cited by 817
Mass Spectrometry as a Diagnostic and a Cancer Biomarker Discovery Tool
Diamandis, E. P. (2004) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r400007-mcp200 · Cited by 631
Metadata
- Authors
- Baggerly, K. A., Morris, J. S., & Coombes, K. R.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2004-01-29
- Volume
- 20
- Issue
- 5
- Pages
- 777-785
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2161371306
- Cited by
- 621
- References
- 9
- FWCI
- 43.31
- Type
- journal article
- Language
- en
- Open access
- bronze
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