{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T19:13:46Z","timestamp":1772738026679,"version":"3.50.1"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031150333","type":"print"},{"value":"9783031150340","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-15034-0_15","type":"book-chapter","created":{"date-parts":[[2022,8,18]],"date-time":"2022-08-18T19:03:08Z","timestamp":1660849388000},"page":"286-293","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Automated Generation of\u00a0Conditional Moment Equations for\u00a0Stochastic Reaction Networks"],"prefix":"10.1007","author":[{"given":"Hanna Josephine","family":"Wiederanders","sequence":"first","affiliation":[]},{"given":"Anne-Lena","family":"Moor","sequence":"additional","affiliation":[]},{"given":"Christoph","family":"Zechner","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,8,19]]},"reference":[{"issue":"3","key":"15_CR1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0149909","volume":"11","author":"J Albert","year":"2016","unstructured":"Albert, J.: A hybrid of the chemical master equation and the Gillespie algorithm for efficient stochastic simulations of sub-networks. PLoS ONE 11(3), e0149909 (2016). https:\/\/doi.org\/10.1371\/journal.pone.0149909","journal-title":"PLoS ONE"},{"key":"15_CR2","doi-asserted-by":"publisher","unstructured":"Bain, A., Crisan, D.: Fundamentals of Stochastic Filtering. Springer, New York (2009). https:\/\/doi.org\/10.1007\/978-0-387-76896-0","DOI":"10.1007\/978-0-387-76896-0"},{"issue":"6","key":"15_CR3","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.97.062147","volume":"97","author":"L Bronstein","year":"2018","unstructured":"Bronstein, L., Koeppl, H.: Marginal process framework: a model reduction tool for Markov jump processes. Phys. Rev. E 97(6), 062147 (2018). https:\/\/doi.org\/10.1103\/PhysRevE.97.062147","journal-title":"Phys. Rev. E"},{"issue":"16","key":"15_CR4","doi-asserted-by":"publisher","DOI":"10.1063\/1.5021242","volume":"148","author":"L Duso","year":"2018","unstructured":"Duso, L., Zechner, C.: Selected-node stochastic simulation algorithm. J. Chem. Phys. 148(16), 164108 (2018). https:\/\/doi.org\/10.1063\/1.5021242","journal-title":"J. Chem. Phys."},{"key":"15_CR5","doi-asserted-by":"publisher","unstructured":"Duso, L., Zechner, C.: Path mutual information for a class of biochemical reaction networks. In: 2019 IEEE 58th Conference on Decision and Control (CDC), pp. 6610\u20136615. IEEE (2019). https:\/\/doi.org\/10.1109\/CDC40024.2019.9029316","DOI":"10.1109\/CDC40024.2019.9029316"},{"issue":"2","key":"15_CR6","doi-asserted-by":"publisher","first-page":"498","DOI":"10.1016\/j.amc.2005.12.032","volume":"180","author":"S Engblom","year":"2006","unstructured":"Engblom, S.: Computing the moments of high dimensional solutions of the master equation. Appl. Math. Comput. 180(2), 498\u2013515 (2006). https:\/\/doi.org\/10.1016\/j.amc.2005.12.032","journal-title":"Appl. Math. Comput."},{"issue":"18","key":"15_CR7","doi-asserted-by":"publisher","first-page":"2863","DOI":"10.1093\/bioinformatics\/btw229","volume":"32","author":"S Fan","year":"2016","unstructured":"Fan, S., et al.: MEANS: python package for moment expansion approximation, inference and simulation. Bioinformatics 32(18), 2863\u20132865 (2016). https:\/\/doi.org\/10.1093\/bioinformatics\/btw229","journal-title":"Bioinformatics"},{"key":"15_CR8","unstructured":"Gardiner, C.: Stochastic Methods, Springer Series in Synergetics, vol. 4. Springer, Berlin (2009). https:\/\/link.springer.com\/book\/9783540707127"},{"key":"15_CR9","doi-asserted-by":"publisher","unstructured":"Gillespie, D.T.: Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem. 81(25), 2340\u20132361 (1977). https:\/\/doi.org\/10.1021\/j100540a008","DOI":"10.1021\/j100540a008"},{"issue":"1\u20133","key":"15_CR10","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1016\/0378-4371(92)90283-V","volume":"188","author":"DT Gillespie","year":"1992","unstructured":"Gillespie, D.T.: A rigorous derivation of the chemical master equation. Physica A 188(1\u20133), 404\u2013425 (1992). https:\/\/doi.org\/10.1016\/0378-4371(92)90283-V","journal-title":"Physica A"},{"issue":"3","key":"15_CR11","doi-asserted-by":"publisher","first-page":"687","DOI":"10.1007\/s00285-013-0711-5","volume":"69","author":"J Hasenauer","year":"2013","unstructured":"Hasenauer, J., Wolf, V., Kazeroonian, A., Theis, F.J.: Method of conditional moments (MCM) for the chemical master equation. J. Math. Biol. 69(3), 687\u2013735 (2013). https:\/\/doi.org\/10.1007\/s00285-013-0711-5","journal-title":"J. Math. Biol."},{"key":"15_CR12","unstructured":"Hespanha, J.P.: StochDynTools \u2013 a MATLAB toolbox to compute moment dynamics for stochastic networks of bio-chemical reactions, May 2007. https:\/\/web.ece.ucsb.edu\/~hespanha\/software\/stochdyntool.html"},{"key":"15_CR13","doi-asserted-by":"crossref","unstructured":"van Kampen, N.G.: Stochastic Processes in Physics and Chemistry. Elsevier, 3rd (edn.) (2007)","DOI":"10.1016\/B978-044452965-7\/50006-4"},{"issue":"1","key":"15_CR14","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0146732","volume":"11","author":"A Kazeroonian","year":"2016","unstructured":"Kazeroonian, A., Fr\u00f6hlich, F., Raue, A., Theis, F.J., Hasenauer, J.: CERENA: ChEmical REaction Network Analyzer-a toolbox for the simulation and analysis of stochastic chemical kinetics. PLoS ONE 11(1), e0146732 (2016). https:\/\/doi.org\/10.1371\/journal.pone.0146732","journal-title":"PLoS ONE"},{"issue":"2","key":"15_CR15","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1006\/jtbi.2000.2066","volume":"205","author":"MJ Keeling","year":"2000","unstructured":"Keeling, M.J.: Multiplicative moments and measures of persistence in ecology. J. Theor. Biol. 205(2), 269\u2013281 (2000). https:\/\/doi.org\/10.1006\/jtbi.2000.2066","journal-title":"J. Theor. Biol."},{"key":"15_CR16","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.103","volume":"3","author":"A Meurer","year":"2017","unstructured":"Meurer, A., et al.: SymPy: symbolic computing in Python. PeerJ Comput. Sci. 3, e103 (2017). https:\/\/doi.org\/10.7717\/peerj-cs.103","journal-title":"PeerJ Comput. Sci."},{"issue":"9","key":"15_CR17","doi-asserted-by":"publisher","DOI":"10.1088\/1751-8121\/aa54d9","volume":"50","author":"D Schnoerr","year":"2017","unstructured":"Schnoerr, D., Sanguinetti, G., Grima, R.: Approximation and inference methods for stochastic biochemical kinetics-a tutorial review. J. Phys. Math. Theor. 50(9), 093001 (2017). https:\/\/doi.org\/10.1088\/1751-8121\/aa54d9","journal-title":"J. Phys. Math. Theor."},{"issue":"2","key":"15_CR18","doi-asserted-by":"publisher","first-page":"414","DOI":"10.1109\/TAC.2010.2088631","volume":"56","author":"A Singh","year":"2010","unstructured":"Singh, A., Hespanha, J.P.: Approximate moment dynamics for chemically reacting systems. IEEE Trans. Autom. Control 56(2), 414\u2013418 (2010). https:\/\/doi.org\/10.1109\/TAC.2010.2088631","journal-title":"IEEE Trans. Autom. Control"},{"key":"15_CR19","doi-asserted-by":"publisher","unstructured":"Singh, A., Hespanha, J.P.: Lognormal moment closures for biochemical reactions. In: Proceedings of the 45th IEEE Conference on Decision and Control, pp. 2063\u20132068. IEEE (2006). https:\/\/doi.org\/10.1109\/cdc.2006.376994","DOI":"10.1109\/cdc.2006.376994"},{"key":"15_CR20","doi-asserted-by":"publisher","unstructured":"Sukys, A., Grima, R.: MomentClosure.jl: automated moment closure approximations in Julia. Bioinformatics 38(1), 289\u2013290 (2022). https:\/\/doi.org\/10.1093\/bioinformatics\/btab469","DOI":"10.1093\/bioinformatics\/btab469"},{"issue":"2","key":"15_CR21","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1111\/j.2517-6161.1957.tb00263.x","volume":"19","author":"P Whittle","year":"1957","unstructured":"Whittle, P.: On the use of the normal approximation in the treatment of stochastic processes. J. Roy. Stat. Soc.: Ser. B (Methodol.) 19(2), 268\u2013281 (1957)","journal-title":"J. Roy. Stat. Soc.: Ser. B (Methodol.)"},{"issue":"17","key":"15_CR22","doi-asserted-by":"publisher","first-page":"4729","DOI":"10.1073\/pnas.1517109113","volume":"113","author":"C Zechner","year":"2016","unstructured":"Zechner, C., Seelig, G., Rullan, M., Khammash, M.: Molecular circuits for dynamic noise filtering. Proc. Natl. Acad. Sci. 113(17), 4729\u20134734 (2016). https:\/\/doi.org\/10.1073\/pnas.1517109113","journal-title":"Proc. Natl. Acad. Sci."}],"container-title":["Lecture Notes in Computer Science","Computational Methods in Systems Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-15034-0_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,2]],"date-time":"2024-10-02T01:35:47Z","timestamp":1727832947000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-15034-0_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031150333","9783031150340"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-15034-0_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"19 August 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CMSB","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Methods in Systems Biology","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bucharest","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Romania","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cmsb2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/fmi.unibuc.ro\/en\/cmsb-2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"43","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"13","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"30% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}