High-throughput phenotypic screening, based on high-content imaging,
is increasingly often used as a tool for drug discovery.
Compound screens are used to find hits that produce the desired phenotypes
in relevant cellular assays. Genomic screens are used to elucidate
the underlying molecular pathways and identify suitable drug targets.
Since high-content screening produces a lot of data,
data science approaches such as statistics, machine learning and neural networks
can help interpret the collected data. Just as virtual screening can be performed
in chemoinformatics (learning predictive models for QSAR - quantitative structure-activity relations)
from data obtained through compound screens,
similar approaches can be taken in the context of high-throughput phenotypic screening.

This will be the first event of its kind in the region of Slovenia and Friuli-Venezia-Giulia.
The event will bring together a group of experts covering different topics
in the fields of high-content screening, image analysis,
chemoinformatics and machine learning. This will allow graduate students and researchers
from both academia and industry to familiarize themselves with these cutting-edge topics.
The workshop will have an impact on both the academic and industrial sector in the region
(e.g. biotech companies of all sizes). The workshop is part of the
INTERREG V-A Italy-Slovenia 2014-2020 project TRAIN
(Big Data and Disease Models: A Cross- border Platform for Validated Biotech Industry Kits),
which brings together experts on the topic from academia and industry.