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Identifying Biochemical Reaction Networks From Heterogeneous Datasets
Imperial Coll London, England; Imperial Coll London, England.
University of Cambridge, England; University of Calif Berkeley, CA USA.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
University of Cambridge, England; Luxembourg Centre Syst Biomed, Luxembourg.
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2015 (English)In: 2015 54TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2015, 2525-2530 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we propose a new method to identify biochemical reaction networks (i.e. both reactions and kinetic parameters) from heterogeneous datasets. Such datasets can contain (a) data from several replicates of an experiment performed on a biological system; (b) data measured from a biochemical network subjected to different experimental conditions, for example, changes/perturbations in biological inductions, temperature, gene knock-out, gene over-expression, etc. Simultaneous integration of various datasets to perform system identification has the potential to avoid non-identifiability issues typically arising when only single datasets are used.

Place, publisher, year, edition, pages
IEEE , 2015. 2525-2530 p.
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:liu:diva-133145DOI: 10.1109/CDC.2015.7402596ISI: 000381554502122ISBN: 978-1-4799-7886-1 (print)OAI: oai:DiVA.org:liu-133145DiVA: diva2:1055174
Conference
54th IEEE Conference on Decision and Control (CDC)
Available from: 2016-12-12 Created: 2016-12-09 Last updated: 2016-12-12

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Citation style
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