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Mass Spectrometry Congress 2019 Journal of Chemical Technology and Applications | Volume 3
Page 20
May 20-21, 2019 | Rome, Italy
MASS SPECTROMETRY,
PROTEOMICS AND POLYMER CHEMISTRY
3rd International Conference on OF EXCELLENCE
IN INTERNATIONAL
MEETINGS
YEARS
MULTIVARIATE STATISTICAL TOOLS FOR
THE IDENTIFICATION OF BIOMARKERS:
APPLICATION TO MASS
SPECTROMETRY-BASED APPROACHES
Mass spectrometry based techniques, either coupled or not to a chro-
matographic separation, are high throughput methods providing a
huge amount of information. These techniques are often exploited for the
identification of markers of particular effects, e.g. comparing different groups
of samples in health sciences applications (controls vs pathological, control vs
drug-treated etc.) or in food science (samples stored in different conditions,
exposed to different environmental effects, from different varieties/cultivars/
geographical origins in authentication and traceability studies). The identifi-
cation of biomarkers from complex data like these must be accomplished by
multivariate statistical tools, able to take into consideration the relationships
between the variables (protein counts, analyte signals or concentrations, m/z
signals etc.), to identify pools of markers with the best predictive ability. To
this purpose, pattern recognition methods (Principal Component Analysis
etc.) and classification tools like PLS-DA, Linear Discriminant Analysis, SIMCA,
Ranking-PCA are also coupled to variable selection methods, Support vector
machines etc. can be successfully applied, with a particular attention towards
two different aspects: The exhaustivity of the search for biomarkers, to identi-
fy all possible candidates providing exhaustive information that can be used
to identify deranged pathways; the predictive ability of themodels to identify
pools of biomarkers that can be used as reliable diagnostic markers. Exam-
ples will be provided from different applications: health science, for the iden-
tification of biomarkers of disease or of drug treatment; food science, for the
identification of markers of different storage conditions, of ripening effects,
of geographical origin or variety in authentication studies. The examples will
involve applications from LC-MS/MS, GC-MS and ICP-MS. Some hints will also
be given on data fusion approaches and able to fuse together different sourc-
es of information.
Elisa Robotti, J Chem Tech App 2019, Volume 3
Elisa Robotti gained her PhD in Chemical Scienc-
es in 2005 at the University of Piemonte Orien-
tale, Italy with the thesis on chemometric tools
applied to the field of analytical chemistry. She
won theYoung Researcher Prize of the Division of
Analytical Chemistry of the Italian Chemical Soci-
ety in 2005. Currently she is Associate Professor
of Analytical Chemistry and Chemometrics at the
same University. Her research interests involve in
the development and optimization of analytical
methods (HPLC-MS/MS, GC-MS and ICP-MS), the
development and application of multivariate
strategies for the identification of biomarkers in
health science (proteomics, metabolomics, lipi-
domics and genomics); food and environmental
sciences, experimental design techniques which
was also applied to the industrial optimization of
products and processes. She is the co-author of
more than 80 papers in national and internation-
al magazines (h-index Scopus: 23) and 11 book
chapters. She is the editor of a volume on the
analysis of 2D-PAGE maps. She was participated
in several national and international congresses
and also she is responsible for the research units
in national and international projects.
Elisa Robotti
University of Piemonte Orientale, Italy
BIOGRAPHY