---
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
    orcid: 0000-0002-9041-0905
  - 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_identifier:
  - UT:000340588700008
  dct_language: eng
  dct_publisher: Springer@
  dct_title: Markov chain aggregation and its applications to combinatorial reaction
    networks@
...