To continue our research on systems biology of mitogenesis, we have developed and fitted accordin... more To continue our research on systems biology of mitogenesis, we have developed and fitted according to the experimental data a highly-branched network model of ERK activation in response to EGF stimulation. To produce a network with full number of possible complexes and reactions that may emerge during signal propagation, we used the rule- based software tool in systems biology, BioNetGen 2. Although our network model contains more than 650 complexes and 5500 reactions, we showed the ability the handle this complexity, even using the manual parameter fitting. Analyzing the results of model fitting, we discuss possible details of protein-protein interaction, such as preferable sites/domains for binding one another, sequestration of active enzymes via binding to huge protein complexes etc. Plans for experimental validation of modeling results are also considered. Keywords-systems biology, mitogenic cell signaling, rule- based network modeling, model fitting, protein-protein interaction
e13143 Background: Anticancer Targeted Drugs (ATDs) specifically target one or a few types of tum... more e13143 Background: Anticancer Targeted Drugs (ATDs) specifically target one or a few types of tumor-related molecules in a cell. More than two hundred of ATDs were approved worldwide. They have different mechanisms of action and are effective for different cohorts of patients. However, many individual cases remain poorly responsive and it is of great importance to identify predictive markers of ATD efficacy. Our aim was to develop a platform enabling smart selection of the most efficient ATD therapies. Methods: We generated a second-opinion platform for clinical oncologists termed Oncobox. It is based on the analysis of gene expression profile of a cancer sample in comparison with the corresponding normal tissue biosamples in order to personalize selection of targeted drugs for individual cancer patients. Based on RNA-seq gene expression data, pathway activation levels are calculated and along with the concentrations of molecular target genes products used as predictors of tumor res...
Methods in molecular biology (Clifton, N.J.), 2017
Although modeling of activation kinetics for various cell signaling pathways has reached a high g... more Although modeling of activation kinetics for various cell signaling pathways has reached a high grade of sophistication and thoroughness, most such kinetic models still remain of rather limited practical value for biomedicine. Nevertheless, recent advancements have been made in application of signaling pathway science for real needs of prescription of the most effective drugs for individual patients. The methods for such prescription evaluate the degree of pathological changes in the signaling machinery based on two types of data: first, on the results of high-throughput gene expression profiling, and second, on the molecular pathway graphs that reflect interactions between the pathway members. For example, our algorithm OncoFinder evaluates the activation of molecular pathways on the basis of gene/protein expression data in the objects of the interest.Yet, the question of assessment of the relative importance for each gene product in a molecular pathway remains unclear unless one c...
Methods in molecular biology (Clifton, N.J.), 2017
We propose a biomathematical approach termed OncoFinder (OF) that enables performing both quantit... more We propose a biomathematical approach termed OncoFinder (OF) that enables performing both quantitative and qualitative analyses of the intracellular molecular pathway activation. OF utilizes an algorithm that distinguishes the activator/repressor role of every gene product in a pathway. This method is applicable for the analysis of any physiological, stress, malignancy, and other conditions at the molecular level. OF showed a strong potential to neutralize background-caused differences between experimental gene expression data obtained using NGS, microarray and modern proteomics techniques. Importantly, in most cases, pathway activation signatures were better markers of cancer progression compared to the individual gene products. OF also enables correlating pathway activation with the success of anticancer therapy for individual patients. We further expanded this approach to analyze impact of micro RNAs (miRs) on the regulation of cellular interactome. Many alternative sources provi...
Signalling pathway activation analysis is a powerful approach for extracting biologically relevan... more Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biol...
To continue our research on systems biology of mitogenesis, we have developed and fitted accordin... more To continue our research on systems biology of mitogenesis, we have developed and fitted according to the experimental data a highly-branched network model of ERK activation in response to EGF stimulation. To produce a network with full number of possible complexes and reactions that may emerge during signal propagation, we used the rule-based software tool in systems biology, BioNetGen 2. Although our network model contains more than 650 complexes and 5500 reactions, we showed the ability the handle this complexity, even using the manual parameter fitting. Analyzing the results of model fitting, we discuss possible details of protein-protein interaction, such as preferable sites/domains for binding one another, sequestration of active enzymes via binding to huge protein complexes etc. Plans for experimental validation of modeling results are also considered.
This paper reports on a new utility for development of computational phantoms for Monte Carlo cal... more This paper reports on a new utility for development of computational phantoms for Monte Carlo calculations and data analysis for in vivo measurements of radionuclides deposited in tissues. The individual parameters of each worker can be acquired for an exact geometric representation of his or her anatomy, which is particularly important for low-energy gamma ray emitting sources such as thorium, uranium, plutonium and other actinides. The software discussed here enables automatic creation of an MCNP input data file based on computed tomography (CT) scanning data. The utility was first tested for low- and medium-energy actinide emitters on Livermore phantoms, the mannequins generally used for lung counting, in order to compare the results of simulation and measurement. From these results, the utility's ability to study uncertainties in in vivo calibration were investigated. Calculations and comparison with the experimental data are presented and discussed in this paper.
To continue our research on systems biology of mitogenesis, we have developed and fitted accordin... more To continue our research on systems biology of mitogenesis, we have developed and fitted according to the experimental data a highly-branched network model of ERK activation in response to EGF stimulation. To produce a network with full number of possible complexes and reactions that may emerge during signal propagation, we used the rule- based software tool in systems biology, BioNetGen 2. Although our network model contains more than 650 complexes and 5500 reactions, we showed the ability the handle this complexity, even using the manual parameter fitting. Analyzing the results of model fitting, we discuss possible details of protein-protein interaction, such as preferable sites/domains for binding one another, sequestration of active enzymes via binding to huge protein complexes etc. Plans for experimental validation of modeling results are also considered. Keywords-systems biology, mitogenic cell signaling, rule- based network modeling, model fitting, protein-protein interaction
e13143 Background: Anticancer Targeted Drugs (ATDs) specifically target one or a few types of tum... more e13143 Background: Anticancer Targeted Drugs (ATDs) specifically target one or a few types of tumor-related molecules in a cell. More than two hundred of ATDs were approved worldwide. They have different mechanisms of action and are effective for different cohorts of patients. However, many individual cases remain poorly responsive and it is of great importance to identify predictive markers of ATD efficacy. Our aim was to develop a platform enabling smart selection of the most efficient ATD therapies. Methods: We generated a second-opinion platform for clinical oncologists termed Oncobox. It is based on the analysis of gene expression profile of a cancer sample in comparison with the corresponding normal tissue biosamples in order to personalize selection of targeted drugs for individual cancer patients. Based on RNA-seq gene expression data, pathway activation levels are calculated and along with the concentrations of molecular target genes products used as predictors of tumor res...
Methods in molecular biology (Clifton, N.J.), 2017
Although modeling of activation kinetics for various cell signaling pathways has reached a high g... more Although modeling of activation kinetics for various cell signaling pathways has reached a high grade of sophistication and thoroughness, most such kinetic models still remain of rather limited practical value for biomedicine. Nevertheless, recent advancements have been made in application of signaling pathway science for real needs of prescription of the most effective drugs for individual patients. The methods for such prescription evaluate the degree of pathological changes in the signaling machinery based on two types of data: first, on the results of high-throughput gene expression profiling, and second, on the molecular pathway graphs that reflect interactions between the pathway members. For example, our algorithm OncoFinder evaluates the activation of molecular pathways on the basis of gene/protein expression data in the objects of the interest.Yet, the question of assessment of the relative importance for each gene product in a molecular pathway remains unclear unless one c...
Methods in molecular biology (Clifton, N.J.), 2017
We propose a biomathematical approach termed OncoFinder (OF) that enables performing both quantit... more We propose a biomathematical approach termed OncoFinder (OF) that enables performing both quantitative and qualitative analyses of the intracellular molecular pathway activation. OF utilizes an algorithm that distinguishes the activator/repressor role of every gene product in a pathway. This method is applicable for the analysis of any physiological, stress, malignancy, and other conditions at the molecular level. OF showed a strong potential to neutralize background-caused differences between experimental gene expression data obtained using NGS, microarray and modern proteomics techniques. Importantly, in most cases, pathway activation signatures were better markers of cancer progression compared to the individual gene products. OF also enables correlating pathway activation with the success of anticancer therapy for individual patients. We further expanded this approach to analyze impact of micro RNAs (miRs) on the regulation of cellular interactome. Many alternative sources provi...
Signalling pathway activation analysis is a powerful approach for extracting biologically relevan... more Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biol...
To continue our research on systems biology of mitogenesis, we have developed and fitted accordin... more To continue our research on systems biology of mitogenesis, we have developed and fitted according to the experimental data a highly-branched network model of ERK activation in response to EGF stimulation. To produce a network with full number of possible complexes and reactions that may emerge during signal propagation, we used the rule-based software tool in systems biology, BioNetGen 2. Although our network model contains more than 650 complexes and 5500 reactions, we showed the ability the handle this complexity, even using the manual parameter fitting. Analyzing the results of model fitting, we discuss possible details of protein-protein interaction, such as preferable sites/domains for binding one another, sequestration of active enzymes via binding to huge protein complexes etc. Plans for experimental validation of modeling results are also considered.
This paper reports on a new utility for development of computational phantoms for Monte Carlo cal... more This paper reports on a new utility for development of computational phantoms for Monte Carlo calculations and data analysis for in vivo measurements of radionuclides deposited in tissues. The individual parameters of each worker can be acquired for an exact geometric representation of his or her anatomy, which is particularly important for low-energy gamma ray emitting sources such as thorium, uranium, plutonium and other actinides. The software discussed here enables automatic creation of an MCNP input data file based on computed tomography (CT) scanning data. The utility was first tested for low- and medium-energy actinide emitters on Livermore phantoms, the mannequins generally used for lung counting, in order to compare the results of simulation and measurement. From these results, the utility's ability to study uncertainties in in vivo calibration were investigated. Calculations and comparison with the experimental data are presented and discussed in this paper.
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