uu.seUppsala University Publications
Change search
ReferencesLink to record
Permanent link

Direct link
An Explorative Parameter Sweep: Spatial-temporal Data Mining in Stochastic Reaction-diffusion Simulations
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre. (Hellander Lab)
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Stochastic reaction-diffusion simulations has become an efficient approach for modelling spatial aspects of intracellular biochemical reaction networks. By accounting for intrinsic noise due to low copy number of chemical species, stochastic reaction-diffusion simulations have the ability to more accurately predict and model biological systems. As with many simulations software, exploration of the parameters associated with the model can be needed to yield new knowledge about the underlying system. The exploration can be conducted by executing parameter sweeps for a model. However, with little or no prior knowledge about the modelled system, the effort for practitioners to explore the parameter space can get overwhelming. To account for this problem we perform a feasibility study on an explorative behavioural analysis of stochastic reaction-diffusion simulations by applying spatial-temporal data mining to large parameter sweeps. By reducing individual simulation outputs into a feature space involving simple time series and distribution analytics, we were able to find similar behaving simulations after performing an agglomerative hierarchical clustering.

Place, publisher, year, edition, pages
2016. , 44 p.
Keyword [en]
Big data, feature extraction, clustering, stochastic reaction-diffusion simulation, spatial-temporal, data mining, cloud computing
National Category
Bioinformatics and Systems Biology
URN: urn:nbn:se:uu:diva-280287OAI: oai:DiVA.org:uu-280287DiVA: diva2:910475
Educational program
Master Programme in Bioinformatics
Available from: 2016-03-09 Created: 2016-03-09 Last updated: 2016-03-09Bibliographically approved

Open Access in DiVA

fulltext(5142 kB)174 downloads
File information
File name FULLTEXT01.pdfFile size 5142 kBChecksum SHA-512
Type fulltextMimetype application/pdf

By organisation
Biology Education Centre
Bioinformatics and Systems Biology

Search outside of DiVA

GoogleGoogle Scholar
Total: 174 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 205 hits
ReferencesLink to record
Permanent link

Direct link