Biomedical Engineering Reference
In-Depth Information
(SELDI-TOF) mass spectroscopy, is becoming a leading technology in nd-
ing disease-related proteomic patterns in tissue, blood, or other biological
samples. The data generated by this technology holds invaluable informa-
tion leading to the disease diagnosis and treatment
1;22;26
. However the raw
mass spectrometric data reects not only the protein information but also
noise information. The data processing goal then is to eectively and cor-
rectly obtain the useful information from the MS data for bimarkers discov-
ery. Biomarkers are biological features such as molecules that are indicators
of physiologic state and also of change during a disease process. At the pro-
tein level, distinct changes occur during the transformation of a healthy cell
into a neoplastic cell, including altered expression, dierential protein mod-
ication, changes in specic activity, and aberrant localization, all of which
may aect cellular function. Identifying and understanding these changes
is the underlying theme in cancer proteomics
28
.
Mass spectrometers are ion optical devices that produce a beam of
gas-phase ions from samples. They sort the resulting mixture of ions ac-
cording to their mass-to-charge (m/z) ratios or a derived property, and
provide analog or digital output signals (peaks) from which the mass-to-
charge ratio and intensity (abundance) of each detected ionic species may
be determined. Masses are not measured directly. Mass spectrometers are
m/z analyzers. The mass-to-charge ratio of an ion is obtained by dividing
the mass of the ion (m), by the number of charges (z) that were acquired
during the process of ionization. The mass of a particle is the sum of the
atomic masses (in Dalton) of all the atoms of the elements of which it is
composed.
Mass spectrometers attempt to answer the basic questions of what and
how much is present by determining ionic masses and intensities. MALDI-
TOF MS is emerging as a leading technology in the proteomics revolution.
Indeed, the year 2002 Nobel Prize in chemistry recognized MALDI's ability
to analyze intact biological macromolecules. Though MALDI-TOF MS al-
lows direct measurement of the protein \signature" of tissue, blood, or other
biological samples, and holds tremendous potential for disease diagnosis and
treatment, key challenges still remain in the processing of MALDI MS data.
As shown in Figure 1, MALDI MS data sets from the same sample have
obvious intensity noises, baseline artifacts, and m=z location variations.
Mass spectrometry based proteomics experiments usually comprise a
data generation phase, a data preprocessing phase, and a data analysis
phase. In early applications of MALDI-TOF analyzers, the mass resolution
was poor and the mass accuracy was limited. A mathematical model of
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