{"oa":1,"isi":1,"intvolume":"        69","issue":"3","publisher":"Springer","year":"2014","doi":"10.1007/s00285-013-0738-7","page":"767 - 797","quality_controlled":"1","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication_status":"published","citation":{"chicago":"Ganguly, Arnab, Tatjana Petrov, and Heinz Koeppl. “Markov Chain Aggregation and Its Applications to Combinatorial Reaction Networks.” <i>Journal of Mathematical Biology</i>. Springer, 2014. <a href=\"https://doi.org/10.1007/s00285-013-0738-7\">https://doi.org/10.1007/s00285-013-0738-7</a>.","mla":"Ganguly, Arnab, et al. “Markov Chain Aggregation and Its Applications to Combinatorial Reaction Networks.” <i>Journal of Mathematical Biology</i>, vol. 69, no. 3, Springer, 2014, pp. 767–97, doi:<a href=\"https://doi.org/10.1007/s00285-013-0738-7\">10.1007/s00285-013-0738-7</a>.","ista":"Ganguly A, Petrov T, Koeppl H. 2014. Markov chain aggregation and its applications to combinatorial reaction networks. Journal of Mathematical Biology. 69(3), 767–797.","ieee":"A. Ganguly, T. Petrov, and H. Koeppl, “Markov chain aggregation and its applications to combinatorial reaction networks,” <i>Journal of Mathematical Biology</i>, vol. 69, no. 3. Springer, pp. 767–797, 2014.","apa":"Ganguly, A., Petrov, T., &#38; Koeppl, H. (2014). Markov chain aggregation and its applications to combinatorial reaction networks. <i>Journal of Mathematical Biology</i>. Springer. <a href=\"https://doi.org/10.1007/s00285-013-0738-7\">https://doi.org/10.1007/s00285-013-0738-7</a>","short":"A. Ganguly, T. Petrov, H. Koeppl, Journal of Mathematical Biology 69 (2014) 767–797.","ama":"Ganguly A, Petrov T, Koeppl H. Markov chain aggregation and its applications to combinatorial reaction networks. <i>Journal of Mathematical Biology</i>. 2014;69(3):767-797. doi:<a href=\"https://doi.org/10.1007/s00285-013-0738-7\">10.1007/s00285-013-0738-7</a>"},"external_id":{"isi":["000340588700008"],"arxiv":["1303.4532"]},"scopus_import":"1","author":[{"last_name":"Ganguly","first_name":"Arnab","full_name":"Ganguly, Arnab"},{"orcid":"0000-0002-9041-0905","full_name":"Petrov, Tatjana","id":"3D5811FC-F248-11E8-B48F-1D18A9856A87","first_name":"Tatjana","last_name":"Petrov"},{"last_name":"Koeppl","full_name":"Koeppl, Heinz","first_name":"Heinz"}],"publication":"Journal of Mathematical Biology","oa_version":"Submitted Version","main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1303.4532"}],"acknowledgement":"T. Petrov is supported by SystemsX.ch—the Swiss Inititative for Systems Biology.","_id":"2056","title":"Markov chain aggregation and its applications to combinatorial reaction networks","date_published":"2014-11-20T00:00:00Z","arxiv":1,"date_created":"2018-12-11T11:55:28Z","volume":69,"type":"journal_article","article_processing_charge":"No","publist_id":"4990","language":[{"iso":"eng"}],"month":"11","status":"public","department":[{"_id":"CaGu"},{"_id":"ToHe"}],"day":"20","date_updated":"2025-09-29T11:50:22Z","abstract":[{"lang":"eng","text":"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."}],"fulldoi":"https://doi.org/10.1007/s00285-013-0738-7"}