Wyniki wyszukiwania - Biblioteka Nauki

1

Planning identification experiments for cell signaling pathways: An NF[...]B case study

100%

Fujarewicz K.

|

2010

|

tom Vol. 20, no 4

773-780

EN

Mathematical modeling of cell signaling pathways has become a very important and challenging problem in recent years. The importance comes from possible applications of obtained models. It may help us to understand phenomena appearing in single cells and cell populations on a molecular level. Furthermore, it may help us with the discovery of new drug therapies. Mathematical models of cell signaling pathways take different forms. The most popular way of mathematical modeling is to use a set of nonlinear ordinary differential equations (ODEs). It is very difficult to obtain a proper model. There are many hypotheses about the structure of the model (sets of variables and phenomena) that should be verified. The next step, fitting the parameters of the model, is also very complicated because of the nature of measurements. The blotting technique usually gives only semi-quantitative observations, which are very noisy and collected only at a limited number of time moments. The accuracy of parameter estimation may be significantly improved by a proper experiment design. Recently, we have proposed a gradient-based algorithm for the optimization of a sampling schedule. In this paper we use the algorithm in order to optimize a sampling schedule for the identification of the mathematical model of the NF[...]B regulatory module, known from the literature. We propose a two-stage optimization approach: a gradient-based procedure to find all stationary points and then pair-wise replacement for finding optimal numbers of replicates of measurements. Convergence properties of the presented algorithm are examined.

2

Identification and suboptimal control of heat exchanger using generalized back propagation through time

100%

Fujarewicz K.

|

2000

|

tom Vol. 10, no. 3/4

167-183

EN

This paper deals with a problem of identification and suboptimal control of a counterflow heat exchanger. From the point of view of control theory the heat exchanger is a nonlinear, multidimensional, distributed parameter, dynamical system, and due to its complexity it is difficult to identify it as a black box. In this paper a hybrid model containing neural networks is identified. Its complicated structure makes the analytical calculation of the gradient of performance index with respect to neural network weights very difficult. This problem is solved using a special, structural formulation of sensitivity analysis called generalized back propagation through time (GBPTT). This method is universal, can be used for searching suboptimal parameters (weights) or suboptimal control signals in continuous or discrete time, nonlinear, dynamical systems. Moreover, the presented method is fully mnemonic. The obtained model of the heat exchanger and the same methodology is used during the gradient calculation of the suboptimal control signal of the heat exchanger. Numerical examples are presented.

3

The analysis of chromatin condensation state and transcriptional activity using DNA microarrays

63%

Widłak P. , Fujarewicz K.

|

tom Vol. 6

IP13--19

EN

The DNA microarray-based technique has been developed to semi-quantitatively measure the in vivo global chromatin condensation state at the resolution of a gene. Chromatin was fractionated due to the differential solubility of histone H1-containing and histone H1-free nucleosomes. A set of genes non-randomly distributed between histone H1-free (uncondensed or open) and histone H1-containing (condensed or closed) chromatin fractions has been identified. The transcript levels have been measured for the same group of genes. The correlation between transcriptional activity and chromatin fraction distribution of particular genes has been established.

4

Stability of gene selection methods for multiclass clssification

63%

Student S. , Fujarewicz K.

|

2010

|

tom Vol. 15

101--107

EN

A big problem in applying DNA microarrays for classification is dimension of the dataset. Recently we proposed a gene selection method based on Partial Least Squares (PLS) for searching best genes for classification. The new idea is to use PLS not only as multiclass approach, but to construct more binary selections that use one versus rest and one versus one approaches. Ranked gene lists are highly instable in the sense, that a small change of the data set often leads to big change of the obtained ordered list. In this article, we take a look at the assessment of stability of our approaches. We compare the variability of the obtained ordered lists from proposed methods with well known Recursive Feature Elimination (RFE) method and classical t-test method. This paper focuses on effective identification of informative genes. As a result, a new strategy to find small subset of significant genes is designed. Our results on real cancer data show that our approach has very high accuracy rate for different combinations of classification methods giving in the same time very stable feature rankings.

5

Radiation-induced bystander effects in human leukemic K562 cells in vitr

32%

Konopacka M. , Rogolinski J. , Herok R. , Orlef A. , Fujarewicz K. , Rzeszowska-Wolny J. , Polanska J. , Swierniak A.

|

nr Supplement 1