Examples
You can reproduce the examples listed on this page by yourself! All you need is a
free trial version of PATTERN
EXPERT airspect and the respective spectrum files (see the links below).
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Streptococci
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The so-called "Intact-Cell-MALDI-TOF mass spectrometry" (ICM-MS) is used to characterize microorganisms (among others) by mass spectra
of the complete cells. In this example, the samples are streptococci of 8 different species from 23 different strains.
These streptococci are important components of the human oral bacterial flora. Some of them, the human pathogenic "mutans streptococci",
are crucial for the development of dental caries. The article mentioned below contains some very interesting results obtained from the mass spectra
of these samples.
You may use PATTERN EXPERT airspect for analyzing a number of questions by yourself, which are slightly different:
Assigning the individual spectra to the correct strain of the respective sample can be done with a classification accuracy of 90.8%, as measured with the so-called
"External Cross Validation" procedure of the software. The correct species is assigned for even 97.8% of the spectra.
Just download the airspect Knowledge Base (about 23 MB)
containing the spectra, which can be imported into the software directly.
Literature:
Rupf S, Breitung K, Schellenberger W, Merte K, Kneist S, Eschrich K: Differentiation of mutans streptococci by intact cell matrix-assisted laser
desorption/ionization time-of-flight mass spectrometry. Oral Microbiol Immunol 2005: 20: 267-273.
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Ovarian Cancer
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A promising method for early diagnosis of ovarian cancer in women could consist of classifying mass spectra of blood serum samples.
However, the reproducibility and methods of analysis of these data are a controversial issue (cf. the literature).
With PATTERN EXPERT airspect you can analyze these spectra yourself and check the expected classification accuracy of
the method using the so-called "External Cross Validation" feature of the software. The data are available from the "NCI and FDA Clinical Proteomics Program":
http://home.ccr.cancer.gov/ncifdaproteomics/OvarianDataset4-3-02.zip.
Literature:
Baggerly Keith A., Morrisa Jeffrey S., Edmonson Sarah R, and Coombes Kevin R.: Signal in Noise: Can Experimental
Bias Explain Some Results of Serum Proteomics Tests for Ovarian Cancer?
Petricoin EF, Ardekani AM, Hitt BA, Levine PJ, Fusaro VA, Steinberg SM, et al.:
Use of proteomic patterns in serum to identify ovarian cancer. Lancet 2002;359(9306):572 - 7.
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Prostate Cancer
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Similarly to the previous example, the classification of mass spectra of blood serum samples could yield a powerful method for the early diagnosis
of prostate cancer in men. The analysis shows that even different stages of the disease can be distinguished.
With PATTERN EXPERT airspect you can analyze these spectra yourself and check the expected classification accuracy of
the method using the so-called "External Cross Validation" feature of the software. The data are available from the "NCI and FDA Clinical Proteomics Program".
You can download it here.
Literature:
Petricoin, E. F., 3rd, Ornstein, D. K., Paweletz, C. P., Ardekani, A., Hackett,P. S., Hitt, B. A., Velassco, A., Trucco, C.,
Wiegand, L., Wood, K., Simone, C. B., Levine, P. J., Linehan, W. M., Emmert-Buck, M. R., Steinberg, S. M., Kohn, E. C., and
Liotta, L. A. (2002) Serum proteomic patterns for detection of prostate cancer. J. Natl. Cancer Inst. 94, 1576 - 1578.
Wright Michael E., Han David K. , and Aebersold Ruedi (2005) Mass Spectrometry-based Expression
Profiling of Clinical Prostate Cancer Molecular & Cellular Proteomics 4:545 - 554.
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Ion Mobility Spectrometry
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Coffee Fragrance
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Different coffees can be distinguished by their "fragrances" using ion mobility spectrometry and PATTERN EXPERT airspect!
Spectra of 9 different coffees from 6 different brands were recorded (3 spectra of each coffee). Thus, the task is to distinguish
9 classes with 3 reference spectra for each class. The so-called "External Cross Validation" procedure of PATTERN EXPERT airspect has
determined a classification accuracy of 81.8%. The only errors were between coffees of one and the same brand.
Although in general a significantly larger number of spectra per class is necessary to construct a reliable classification system,
this demonstration example shows that fairly good results can be achieved with very low effort.
The measurements have been made with an ion mobility spectrometer of G.A.S. (Dortmund, Germany).
Ion mobility spectrometry (IMS) is an inexpensive and efficient method for analyzing gas, "smells", "fragrances", etc.
The spectra are available here.
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