Alireza Tamaddoni-Nezhad, Stephen Muggleton
This paper describes the use of a mixture of abduction
and induction for the problem of identifying
the effects of toxins in metabolic networks. Background
knowledge is used which describes network
topology and functional classes of enzymes.
This background knowledge, which represents the
present state of understanding, is incomplete. In
order to overcome this incompleteness hypotheses
are entertained which consist of a mixture of
specific inhibitions of enzymes (ground facts) together
with general rules which predict classes of
enzymes likely to be inhibited by the toxin (nonground).
The foreground examples were derived
from in vivo experiments involving NMR analysis
of time-varying metabolite concentrations in rat
urine following injections of toxin. Hypotheses
about inhibition are built using Progol5.0 and predictive
accuracy is assessed for both the ground and
the non-ground cases.
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