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Feature-selection techniques and modeling approaches in QSAR and QSPR

Thursday, 24 May, 2012 - 17:00
Campus: Brussels Health Campus
Faculty: Medicine and Pharmacy
auditorium 5
Mohammad Goodarzi
phd defence

A Quantitative Structure–Activity Relationship
(QSAR) is a linear or nonlinear model, which
relates variations in molecular descriptors
(containing information about the structure) to
variations in biological activity using a series of
active and/or inactive compounds. It can either
be used for prediction of the activity of untested
drugs or to set up a priority plan of synthesis and
experimental testing of new compounds. There
are several steps which are important to build a
QSAR/QSPR models. For instance, the feature
selection and the modeling are two of them.

The selection of the relevant molecular
descriptors from more than one thousand
calculated descriptors is a crucial step in the
development of QSAR models. In spite of the fact
that many feature-selection methods already
have been applied, it is still unclear which to use
best to find a stable and reliable feature selection
for a given type of data set.

The main aim of the thesis was to compare
different feature-selection and modeling
techniques in QSAR/QSPR studies.