Аннотация
Discrete temporal transitions occur in a variety of domains, but this
work is mainly motivated by applications in molecular biology:
explaining and analyzing observed transcriptome and proteome time
series by literature and database knowledge. The starting point of a
formal concept analysis model is presented. The objects of a formal
context are states of the interesting entities, and the attributes are
the variable properties defining the current state (e.g. observed
presence or absence of proteins). Temporal transitions assign a
relation to the objects, defined by deterministic or non-deterministic
transition rules between sets of preand postconditions. This relation
can be generalized to its transitive closure, i.e. states are related
if one results from the other by a transition sequence of arbitrary
length. The focus of the work is the adaptation of the attribute
exploration algorithm to such a relational context, so that questions
concerning temporal dependencies can be asked during the exploration
process and be answered from the computed stem base. Results are given
for the abstract example of a game and a small gene regulatory network
relevant to a biomedical question. 1
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