---
res:
bibo_abstract:
- 'We consider a continuous-time Markov chain (CTMC) whose state space is partitioned
into aggregates, and each aggregate is assigned a probability measure. A sufficient
condition for defining a CTMC over the aggregates is presented as a variant of
weak lumpability, which also characterizes that the measure over the original
process can be recovered from that of the aggregated one. We show how the applicability
of de-aggregation depends on the initial distribution. The application section
is devoted to illustrate how the developed theory aids in reducing CTMC models
of biochemical systems particularly in connection to protein-protein interactions.
We assume that the model is written by a biologist in form of site-graph-rewrite
rules. Site-graph-rewrite rules compactly express that, often, only a local context
of a protein (instead of a full molecular species) needs to be in a certain configuration
in order to trigger a reaction event. This observation leads to suitable aggregate
Markov chains with smaller state spaces, thereby providing sufficient reduction
in computational complexity. This is further exemplified in two case studies:
simple unbounded polymerization and early EGFR/insulin crosstalk.@eng'
bibo_authorlist:
- foaf_Person:
foaf_givenName: Arnab
foaf_name: Ganguly, Arnab
foaf_surname: Ganguly
- foaf_Person:
foaf_givenName: Tatjana
foaf_name: Petrov, Tatjana
foaf_surname: Petrov
foaf_workInfoHomepage: http://www.librecat.org/personId=3D5811FC-F248-11E8-B48F-1D18A9856A87
- foaf_Person:
foaf_givenName: Heinz
foaf_name: Koeppl, Heinz
foaf_surname: Koeppl
bibo_doi: 10.1007/s00285-013-0738-7
bibo_issue: '3'
bibo_volume: 69
dct_date: 2014^xs_gYear
dct_language: eng
dct_publisher: Springer@
dct_title: Markov chain aggregation and its applications to combinatorial reaction
networks@
...