Regulatory Relations Represented in Logics and Biomedical Texts

Regulatory networks are used for simple modeling of varying complexity,
for example within biology, economics and other elds that apply dynamic
systems.
In biomedicine, regulatory networks are widely used to model regulatory
pathways, which, in short, are characterized by processes containing gene
products and smaller molecules that regulate each other through dierent
mechanisms through dierent paths. The relations between the building
blocks of these networks are typically modeled either very expressively or
very simply in graphs in information systems.
The focus of this dissertation is the biomedical semantics of regulates
relations, i.e. positively regulates, negatively regulates and regulates, of which
is assumed to be a super relation of the rst two.
This thesis discusses an initial framework for knowledge representation
based on logics, carries out a corpus analysis on the verbs representing regulation
(positively and negatively) and denes four rules of reasoning. Compositions
within class relationship logic have also been explored.
One of the main goals of this dissertation is to form a foundational basis
of knowledge on regulation that contributes to the further development of
information services on regulatory events within biomedicine.