Object
Title: Properties of a singular value decomposition based dynamical model of gene expression data
Contributor:
Kimmel, Marek - red. ; Lachowicz, Mirosław - red. ; Świerniak, Andrzej - red.
Subtitle:
Cancer Growth and Progression, Mathematical Problems and Computer Simulations
Group publication title:
Abstract:
Recently, data on multiple gene expression at sequential time points were analyzed using the Singular Value Decomposition (SVD) as a means to capture dominant trends, called characteristic modes, followed by the fitting of a linear discrete-time dynamical system in which the expression values at a given time point are linear combinations of the values at a previous time point. ; We attempt to address several aspects of the method. To obtain the model, we formulate a nonlinear optimization problem and present how to solve it numerically using the standardMATLAB procedures. We use freely available data to test the approach. ; We discuss the possible consequences of data regularization, called sometimes "polishing", on the outcome of the analysis, especially when the model is to be used for prediction purposes. Then, we investigate the sensitivity of the method to missing measurements and its abilities to reconstruct the missing data. ; Summarizing, we point out that approximation of multiple gene expression data preceded by SVD provides some insight into the dynamics, but may also lead to unexpected difficulties, like overfitting problems.
Publisher:
Zielona Góra: Uniwersytet Zielonogórski
Resource Identifier:
Pages:
Source:
AMCS, volume 13, number 3 (2003) ; click here to follow the link
Language:
Rights:
Biblioteka Uniwersytetu Zielonogórskiego
Object collections:
- Digital Library of Zielona Góra > Repository > Faculties > Faculty of Computer, Electrical and Control Engineering
- Digital Library of Zielona Góra > Repository > Types of work > Articles
- Digital Library of Zielona Góra > Repository > Scientific journals and UZ publishing series > International Journal of Applied Mathematics and Computer Science (AMCS)
- Digital Library of Zielona Góra > Repository > Scientific journals and UZ publishing series > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (2003)
Last modified:
Oct 18, 2021
In our library since:
Oct 18, 2021
Number of object content hits:
101
All available object's versions:
https://zbc.uz.zgora.pl/publication/65908
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International Journal of Applied Mathematics and Computer Science (AMCS)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 26 (2016)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 25 (2015)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 24 (2014)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 23 (2013)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 22 (2012)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 21 (2011)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 20 (2010)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 19 (2009)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 18 (2008)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 17 (2007)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 16 (2006)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 15 (2005)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 13 (2003)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 13, number 1 (2003)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 13, number 2 (2003)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 13, number 3 (2003)
- Stochastic models of progression of cancer and their use in controlling cancer-related mortality
- Mathematical modeling of the competition between acquired immunity and cancer
- Different models of chemotherapy taking into account drug resistance stemming from gene amplification
- Modelling tumour-immunity interactions with different stimulation functions
- Logistic equations in tumour growth modelling
- Selecting differentially expressed genes for colon tumor classification
- Properties of a singular value decomposition based dynamical model of gene expression data
- Population genetics models for the statistics of DNA samples under different demographic scenarios - Maximum likelihood versus approximate methods
- Optimal control for a class of compartmental models in cancer chemotherapy
- Application of the adaptive center-weighted vector median framework for the enhancement of cDNA microarray images
- Sampling properties of estimators of nucleotide diversity at discovered SNP sites
- Dynamics of the tumor - immune system competition - the effect of time delay
- Analysis of immunotherapy models in the context of cancer dynamics
- The EM algorithm and its implementation for the estimation of frequencies of SNP-haplotypes
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 13, number 4 (2003)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 13, number 1 (2003)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 7 (1997)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 6 (1996)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 5 (1995)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 4 (1994)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 2 (1992)
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International Journal of Applied Mathematics and Computer Science (AMCS),volume 1 (1991)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 26 (2016)
| Edition name | Date |
|---|---|
| Properties of a singular value decomposition based dynamical model of gene expression data | Oct 18, 2021 |
