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Qualitative assessment of cDNA microarray gene expression data using detrended fluctuation analysis

Nagarajan, Radhakrishnan; Upreti, Meenakshi; Govindan, R.B. - In: Physica A: Statistical Mechanics and its Applications 373 (2007) C, pp. 503-510

A number of microarray studies assume gene expression data to be independent of one another. In this report, we provide … evidence of correlation in cDNA microarray gene expression data using classical power spectral analysis and the sophisticated … assessment of microarray gene expression data prior to inferring differential gene expression. …

Persistent link: https://www.econbiz.de/10010591106

Modeling the Human Genome Maintenance network

Simão, Éder M.; Cabral, Heleno B.; Castro, Mauro A.A.; … - In: Physica A: Statistical Mechanics and its Applications 389 (2010) 19, pp. 4188-4194

microarray study of adenoma to identify the regions of the network that are highly altered. In the last application we present …

Persistent link: https://www.econbiz.de/10011062311

High-gain nonlinear observer for simple genetic regulation process

Torres, L.A.; Ibarra-Junquera, V.; Escalante-Minakata, P.; … - In: Physica A: Statistical Mechanics and its Applications 380 (2007) C, pp. 235-240

High-gain nonlinear observers occur in the nonlinear automatic control theory and are in standard usage in chemical engineering processes. We apply such a type of analysis in the context of a very simple one-gene regulation circuit. In general, an observer combines an analytical...

Persistent link: https://www.econbiz.de/10010873819

Effect of environmental stress on regulation of gene expression in the yeast

Gross, Eitan - In: Physica A: Statistical Mechanics and its Applications 430 (2015) C, pp. 224-235

Several mathematical models have been proposed to predict the activation state of a transcription factor (TF) from the expression levels of its target genes. This inference problem is complicated however due to the fact that different genes may be regulated by different activation schemes...

Persistent link: https://www.econbiz.de/10011264539

A recursive network approach can identify constitutive regulatory circuits in gene expression data

Blasi, Monica Francesca; Casorelli, Ida; Colosimo, Alfredo - In: Physica A: Statistical Mechanics and its Applications 348 (2005) C, pp. 349-370

identification of the regulative programmes from microarray experiments is limited, however, by the intrinsic difficulty of linear … stability genes. The proposed method, by greatly enhancing the sensitivity of microarray studies, allows the identification of …

Persistent link: https://www.econbiz.de/10010588977

Algorithms of maximum likelihood data clustering with applications

Giada, Lorenzo; Marsili, Matteo - In: Physica A: Statistical Mechanics and its Applications 315 (2002) 3, pp. 650-664

We address the problem of data clustering by introducing an unsupervised, parameter-free approach based on maximum likelihood principle. Starting from the observation that data sets belonging to the same cluster share a common information, we construct an expression for the likelihood of any...

Persistent link: https://www.econbiz.de/10010590077

Emergence of the self-similar property in gene expression dynamics

Ochiai, T.; Nacher, J.C.; Akutsu, T. - In: Physica A: Statistical Mechanics and its Applications 382 (2007) 2, pp. 739-752

Many theoretical models have recently been proposed to understand the structure of cellular systems composed of various types of elements (e.g., proteins, metabolites and genes) and their interactions. However, the cell is a highly dynamic system with thousands of functional elements fluctuating...

Persistent link: https://www.econbiz.de/10010590543

Clustering gene expression by dynamics: A maximum entropy approach

Diambra, L. - In: Physica A: Statistical Mechanics and its Applications 387 (2008) 8, pp. 2187-2196

Arrays allow simultaneous measurements of the expression levels of thousands of mRNAs. By mining this data one can identify sets of genes with similar profiles. We show that information theoretic methods are capable of modeling and assessing dissimilarities between the dynamics underlying to the...

Persistent link: https://www.econbiz.de/10010591703