Data-Informed Parameter Synthesis for Population Markov Chains

Hajnal, Matej; Nouvian, Morgane; Petrov, Tatjana; Safranek, David

Data-Informed Parameter Synthesis for Population Markov Chains

Dateien

Zu diesem Dokument gibt es keine Dateien.

Datum

2019

Autor:innen

Hajnal, Matej

Nouvian, Morgane

Petrov, Tatjana

Safranek, David

DOI (zitierfähiger Link)

https://doi.org/10.1007/978-3-030-31304-3_32

Sammlungen

Biologie
Exzellenzcluster "Centre for the Advanced Study of Collective Behaviour"
Informatik und Informationswissenschaft

Publikationstyp

Beitrag zu einem Konferenzband

Publikationsstatus

Published

Erschienen in

BORTOLUSSI, Luca, ed., Guido SANGUINETTI, ed.. Computational methods in systems biology : 17th international conference, CMSB 2019, Trieste, Italy, September 18-20, 2019 : proceedings. Cham: Springer, 2019, pp. 383-386. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-31303-6. Available under: doi: 10.1007/978-3-030-31304-3_32

Zusammenfassung

Population models are widely used to model different phenomena: animal collectives such as social insects, flocking birds, schooling fish, or humans within societies, as well as molecular species inside a cell, cells forming a tissue. Animal collectives show remarkable self-organisation towards emergent behaviours without centralised control. Quantitative models of the underlying mechanisms can directly serve important societal concerns (for example, prediction of seismic activity [5]), inspire the design of distributed algorithms (for example, ant colony algorithm [1]), or aid robust design and engineering of collective, adaptive systems under given functionality and resources, which is recently gaining attention in vision of smart cities [3, 4]. Quantitative prediction of the behaviour of a population of agents over time and space, each having several behavioural modes, results in a high-dimensional, non-linear, and stochastic system [2]. Hence, computational modelling with population models is challenging, especially when the model parameters are unknown and experiments are expensive.

Fachgebiet (DDC)

570 Biowissenschaften, Biologie

Konferenz

17th international conference, CMSB 2019, 18. Sep. 2019 - 20. Sep. 2019, Trieste, Italy

Zitieren

ISO 690

HAJNAL, Matej, Morgane NOUVIAN, Tatjana PETROV, David SAFRANEK, 2019. Data-Informed Parameter Synthesis for Population Markov Chains. 17th international conference, CMSB 2019. Trieste, Italy, 18. Sep. 2019 - 20. Sep. 2019. In: BORTOLUSSI, Luca, ed., Guido SANGUINETTI, ed.. Computational methods in systems biology : 17th international conference, CMSB 2019, Trieste, Italy, September 18-20, 2019 : proceedings. Cham: Springer, 2019, pp. 383-386. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-31303-6. Available under: doi: 10.1007/978-3-030-31304-3_32

BibTex

@inproceedings{Hajnal2019-09-17DataI-50675,
  year={2019},
  doi={10.1007/978-3-030-31304-3_32},
  title={Data-Informed Parameter Synthesis for Population Markov Chains},
  number={11773},
  isbn={978-3-030-31303-6},
  issn={0302-9743},
  publisher={Springer},
  address={Cham},
  series={Lecture Notes in Computer Science / Lecture notes in bioinformatics},
  booktitle={Computational methods in systems biology : 17th international conference, CMSB 2019, Trieste, Italy, September 18-20, 2019 : proceedings},
  pages={383--386},
  editor={Bortolussi, Luca and Sanguinetti, Guido},
  author={Hajnal, Matej and Nouvian, Morgane and Petrov, Tatjana and Safranek, David}
}

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Universitätsbibliographie

Ja