Peak Scores Significantly Depend on the Relationships between Contextual Signals in ChIP-Seq Peaks.

Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) is a central genome-wide method for in vivo analyses of DNA-protein interactions in various cellular conditions. Numerous studies have demonstrated the complex contextual organization of ChIP-seq peak sequences and the presence of binding sites for transcription factors in them. We assessed the dependence of the ChIP-seq peak score on the presence of different contextual signals in the peak sequences by analyzing these sequences from several ChIP-seq experiments using our fully enumerative GPU-based de novo motif discovery method, Argo_CUDA. Analysis revealed sets of significant IUPAC motifs corresponding to the binding sites of the target and partner transcription factors. For these ChIP-seq experiments, multiple regression models were constructed, demonstrating a significant dependence of the peak scores on the presence in the peak sequences of not only highly significant target motifs but also less significant motifs corresponding to the binding sites of the partner transcription factors. A significant correlation was shown between the presence of the target motifs FOXA2 and the partner motifs HNF4G, which found experimental confirmation in the scientific literature, demonstrating the important contribution of the partner transcription factors to the binding of the target transcription factor to DNA and, consequently, their important contribution to the peak score.

Clinical Response to Personalized Exercise Therapy in Heart Failure Patients with Reduced Ejection Fraction is Accompanied by Skeletal Muscle Histological Alterations.

Abstract: Heart failure (HF) is associated with skeletal muscle wasting and exercise intolerance. This study aimed to evaluate the exercise-induced clinical response and histological alterations. One hundred and forty-four HF patients were enrolled. The individual training program was determined as a workload at or close to the lactate threshold (LT1); clinical data were collected before and after 12 weeks/6 months of training. The muscle biopsies from eight patients were taken before and after 12 weeks of training: histology analysis was used to evaluate muscle morphology. Most of the patients demonstrated a positive response after 12 weeks of the physical rehabilitation program in one or several parameters tested, and 30% of those showed improvement in all four of the following parameters: oxygen uptake (VO2) peak, left ventricular ejection fraction (LVEF), exercise tolerance (ET), and quality of life (QOL); the walking speed at LT1 after six months of training showed a significant rise. Along with clinical response, the histological analysis detected a small but significant decrease in both fiber and endomysium thickness after the exercise training course indicating the stabilization of muscle mechanotransduction system. Together, our data show that the beneficial effect of personalized exercise therapy in HF patients depends, at least in part, on the improvement in skeletal muscle physiological and biochemical performance.

Haplotype analysis of APOE intragenic SNPs.

BACKGROUND: APOE Îµ4 allele is most common genetic risk factor for Alzheimer's disease (AD) and cognitive decline. However, it remains poorly understood why only some carriers of APOE Îµ4 develop AD and how ethnic variabilities in APOE locus contribute to AD risk. Here, to address the role of APOE haplotypes, we reassessed the diversity of APOE locus in major ethnic groups and in Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset on patients with AD, and subjects with mild cognitive impairment (MCI), and control non-demented individuals. RESULTS: We performed APOE gene haplotype analysis for a short block of five SNPs across the gene using the ADNI whole genome sequencing dataset. The compilation of ADNI data with 1000 Genomes identified the APOE ε4 linked haplotypes, which appeared to be distant for the Asian, African and European populations. The common European ε4-bearing haplotype is associated with AD but not with MCI, and the Africans lack this haplotype. Haplotypic inference revealed alleles that may confer protection against AD. By assessing the DNA methylation profile of the APOE haplotypes, we found that the AD-associated haplotype features elevated APOE CpG content, implying that this locus can also be regulated by genetic-epigenetic interactions. CONCLUSIONS: We showed that SNP frequency profiles within APOE locus are highly skewed to population-specific haplotypes, suggesting that the ancestral background within different sites at APOE gene may shape the disease phenotype. We propose that our results can be utilized for more specific risk assessment based on population descent of the individuals and on higher specificity of five site haplotypes associated with AD.

Notch-dependent EMT is attenuated in patients with aortic aneurysm and bicuspid aortic valve.

Bicuspid aortic valve is the most common congenital heart malformation and the reasons for the aortopathies associated with bicuspid aortic valve remain unclear. NOTCH1 mutations are associated with bicuspid aortic valve and have been found in individuals with various left ventricular outflow tract abnormalities. Notch is a key signaling during cardiac valve formation that promotes the endothelial-to-mesenchymal transition. We address the role of Notch signaling in human aortic endothelial cells from patients with bicuspid aortic valve and aortic aneurysm. Aortic endothelial cells were isolated from tissue fragments of bicuspid aortic valve-associated thoracic aortic aneurysm patients and from healthy donors. Endothelial-to-mesenchymal transition was induced by activation of Notch signaling. Effectiveness of the transition was estimated by loss of endothelial and gain of mesenchymal markers by immunocytochemistry and qPCR. We show that aortic endothelial cells from the patients with aortic aneurysm and bicuspid aortic valve have down regulated Notch signaling and fail to activate Notch-dependent endothelial-to-mesenchymal transition in response to its stimulation by different Notch ligands. Our findings support the idea that bicuspid aortic valve and associated aortic aneurysm is associated with dysregulation of the entire Notch signaling pathway independently on the specific gene mutation.

A database of human genes and a gene network involved in response to tick-borne encephalitis virus infection.

BACKGROUND: Tick-borne encephalitis is caused by the neurotropic, positive-sense RNA virus, tick-borne encephalitis virus (TBEV). TBEV infection can lead to a variety of clinical manifestations ranging from slight fever to severe neurological illness. Very little is known about genetic factors predisposing to severe forms of disease caused by TBEV. The aims of the study were to compile a catalog of human genes involved in response to TBEV infection and to rank genes from the catalog based on the number of neighbors in the network of pairwise interactions involving these genes and TBEV RNA or proteins. RESULTS: Based on manual review and curation of scientific publications a catalog comprising 140 human genes involved in response to TBEV infection was developed. To provide access to data on all genes, the TBEVhostDB web resource ( http://icg.nsc.ru/TBEVHostDB/ ) was created. We reconstructed a network formed by pairwise interactions between TBEV virion itself, viral RNA and viral proteins and 140 genes/proteins from TBEVHostDB. Genes were ranked according to the number of interactions in the network. Two genes/proteins (CCR5 and IFNAR1) that had maximal number of interactions were revealed. It was found that the subnetworks formed by CCR5 and IFNAR1 and their neighbors were a fragments of two key pathways functioning during the course of tick-borne encephalitis: (1) the attenuation of interferon-I signaling pathway by the TBEV NS5 protein that targeted peptidase D; (2) proinflammation and tissue damage pathway triggered by chemokine receptor CCR5 interacting with CD4, CCL3, CCL4, CCL2. Among nine genes associated with severe forms of TBEV infection, three genes/proteins (CCR5, IL10, ARID1B) were found to have protein-protein interactions within the network, and two genes/proteins (IFNL3 and the IL10, that was just mentioned) were up- or down-regulated in response to TBEV infection. Based on this finding, potential mechanisms for participation of CCR5, IL10, ARID1B, and IFNL3 in the host response to TBEV infection were suggested. CONCLUSIONS: A database comprising 140 human genes involved in response to TBEV infection was compiled and the TBEVHostDB web resource, providing access to all genes was created. This is the first effort of integrating and unifying data on genetic factors that may predispose to severe forms of diseases caused by TBEV. The TBEVHostDB could potentially be used for assessment of risk factors for severe forms of tick-borne encephalitis and for the design of personalized pharmacological strategies for the treatment of TBEV infection.

A compendium and functional characterization of mammalian genes involved in adaptation to Arctic or Antarctic environments.

BACKGROUND: Many mammals are well adapted to surviving in extremely cold environments. These species have likely accumulated genetic changes that help them efficiently cope with low temperatures. It is not known whether the same genes related to cold adaptation in one species would be under selection in another species. The aims of this study therefore were: to create a compendium of mammalian genes related to adaptations to a low temperature environment; to identify genes related to cold tolerance that have been subjected to independent positive selection in several species; to determine promising candidate genes/pathways/organs for further empirical research on cold adaptation in mammals. RESULTS: After a search for publications containing keywords: "whole genome", "transcriptome or exome sequencing data", and "genome-wide genotyping array data" authors looked for information related to genetic signatures ascribable to positive selection in Arctic or Antarctic mammalian species. Publications related to Human, Arctic fox, Yakut horse, Mammoth, Polar bear, and Minke whale were chosen. The compendium of genes that potentially underwent positive selection in >1 of these six species consisted of 416 genes. Twelve of them showed traces of positive selection in three species. Gene ontology term enrichment analysis of 416 genes from the compendium has revealed 13 terms relevant to the scope of this study. We found that enriched terms were relevant to three major groups: terms associated with collagen proteins and the extracellular matrix; terms associated with the anatomy and physiology of cilium; terms associated with docking. We further revealed that genes from compendium were over-represented in the lists of genes expressed in the lung and liver. CONCLUSIONS: A compendium combining mammalian genes involved in adaptation to cold environment was designed, based on the intersection of positively selected genes from six Arctic and Antarctic species. The compendium contained 416 genes that have been positively selected in at least two species. However, we did not reveal any positively selected genes that would be related to cold adaptation in all species from our list. But, our work points to several strong candidate genes involved in mechanisms and biochemical pathways related to cold adaptation response in different species.

A compendium of human genes regulating feeding behavior and body weight, its functional characterization and identification of GWAS genes involved in brain-specific PPI network.

BACKGROUND: Obesity is heritable. It predisposes to many diseases. The objectives of this study were to create a compendium of genes relevant to feeding behavior (FB) and/or body weight (BW) regulation; to construct and to analyze networks formed by associations between genes/proteins; and to identify the most significant genes, biological processes/pathways, and tissues/organs involved in BW regulation. RESULTS: The compendium of genes controlling FB or BW includes 578 human genes. Candidate genes were identified from various sources, including previously published original research and review articles, GWAS meta-analyses, and OMIM (Online Mendelian Inheritance in Man). All genes were ranked according to knowledge about their biological role in body weight regulation and classified according to expression patterns or functional characteristics. Substantial and overrepresented numbers of genes from the compendium encoded cell surface receptors, signaling molecules (hormones, neuropeptides, cytokines), transcription factors, signal transduction proteins, cilium and BBSome components, and lipid binding proteins or were present in the brain-specific list of tissue-enriched genes identified with TSEA tool. We identified 27 pathways from KEGG, REACTOME and BIOCARTA whose genes were overrepresented in the compendium. Networks formed by physical interactions or homological relationships between proteins or interactions between proteins involved in biochemical/signaling pathways were reconstructed and analyzed. Subnetworks and clusters identified by the MCODE tool included genes/proteins associated with cilium morphogenesis, signal transduction proteins (particularly, G protein-coupled receptors, kinases or proteins involved in response to insulin stimulus) and transcription regulation (particularly nuclear receptors). We ranked GWAS genes according to the number of neighbors in three networks and revealed 22 GWAS genes involved in the brain-specific PPI network. On the base of the most reliable PPIs functioning in the brain tissue, new regulatory schemes interpreting relevance to BW regulation are proposed for three GWAS genes (ETV5, LRP1B, and NDUFS3). CONCLUSIONS: A compendium comprising 578 human genes controlling FB or BW was designed, and the most significant functional groups of genes, biological processes/pathways, and tissues/organs involved in BW regulation were revealed. We ranked genes from the GWAS meta-analysis set according to the number and quality of associations in the networks and then according to their involvement in the brain-specific PPI network and proposed new regulatory schemes involving three GWAS genes (ETV5, LRP1B, and NDUFS3) in BW regulation. The compendium is expected to be useful for pathology risk estimation and for design of new pharmacological approaches in the treatment of human obesity.

A Catalog of Human Genes Associated With Pathozoospermia and Functional Characteristics of These Genes.

Genetic causes of the global decline in male fertility are among the hot spots of scientific research in reproductive genetics. The most common way to evaluate male fertility in clinical trials is to determine semen quality. Lower semen quality is very often accompanied by subfertility or infertility, occurs in many diseases and can be caused by many factors, including genetic ones. The following forms of lowered semen quality (pathozoospermia) are known: azoospermia, oligozoospermia, asthenozoospermia, teratozoospermia, and some combined forms. To systematize information about the genetic basis of impaired spermatogenesis, we created a catalog of human genes associated with lowered semen quality (HGAPat) and analyzed their functional characteristics. The catalog comprises data on 126 human genes. Each entry of the catalog describes an association between an allelic variant of the gene and a particular form of lowered semen quality, extracted from the experimental study. Most genes included into the catalog are located on autosomes and are associated with such pathologies as non-obstructive azoospermia, oligozoospermia or asthenozoospermia. Slightly less than half of the included genes (43%) are expressed in the testes in a tissue-specific manner. Functional annotation of genes from the catalog showed that spermatogenic failure can be associated with mutations in genes that control biological processes essential for spermiogenesis (regulating DNA metabolism, cell division, formation of cellular structures, which provide cell movement) as well as with mutations in genes that control cellular responses to unfavorable conditions (stress factors, including oxidative stress and exposure to toxins).

Regulatory Action of Plasma from Patients with Obesity and Diabetes towards Muscle Cells Differentiation and Bioenergetics Revealed by the C2C12 Cell Model and MicroRNA Analysis.

Obesity and type 2 diabetes mellitus (T2DM) are often combined and pathologically affect many tissues due to changes in circulating bioactive molecules. In this work, we evaluated the effect of blood plasma from obese (OB) patients or from obese patients comorbid with diabetes (OBD) on skeletal muscle function and metabolic state. We employed the mouse myoblasts C2C12 differentiation model to test the regulatory effect of plasma exposure at several levels: (1) cell morphology; (2) functional activity of mitochondria; (3) expression levels of several mitochondria regulators, i.e., Atgl, Pgc1b, and miR-378a-3p. Existing databases were used to computationally predict and analyze mir-378a-3p potential targets. We show that short-term exposure to OB or OBD patients' plasma is sufficient to affect C2C12 properties. In fact, the expression of genes that regulate skeletal muscle differentiation and growth was downregulated in both OB- and OBD-treated cells, maximal mitochondrial respiration rate was downregulated in the OBD group, while in the OB group, a metabolic switch to glycolysis was detected. These alterations correlated with a decrease in ATGL and Pgc1b expression in the OB group and with an increase of miR-378a-3p levels in the OBD group.

LMNA Mutations G232E and R482L Cause Dysregulation of Skeletal Muscle Differentiation, Bioenergetics, and Metabolic Gene Expression Profile.

Laminopathies are a family of monogenic multi-system diseases resulting from mutations in the LMNA gene which include a wide range of neuromuscular disorders. Although lamins are expressed in most types of differentiated cells, LMNA mutations selectively affect only specific tissues by mechanisms that remain largely unknown. We have employed the combination of functional in vitro experiments and transcriptome analysis in order to determine how two LMNA mutations associated with different phenotypes affect skeletal muscle development and metabolism. We used a muscle differentiation model based on C2C12 mouse myoblasts genetically modified with lentivirus constructs bearing wild-type human LMNA (WT-LMNA) or R482L-LMNA/G232E-LMNA mutations, linked to familial partial lipodystrophy of the Dunnigan type and muscular dystrophy phenotype accordingly. We have shown that both G232E/R482L-LMNA mutations cause dysregulation in coordination of pathways that control cell cycle dynamics and muscle differentiation. We have also found that R482/G232E-LMNA mutations induce mitochondrial uncoupling and a decrease in glycolytic activity in differentiated myotubes. Both types of alterations may contribute to mutation-induced muscle tissue pathology.

Exome-wide search and functional annotation of genes associated in patients with severe tick-borne encephalitis in a Russian population.

BACKGROUND: Tick-borne encephalitis (TBE) is a viral infectious disease caused by tick-borne encephalitis virus (TBEV). TBEV infection is responsible for a variety of clinical manifestations ranging from mild fever to severe neurological illness. Genetic factors involved in the host response to TBEV that may potentially play a role in the severity of the disease are still poorly understood. In this study, using whole-exome sequencing, we aimed to identify genetic variants and genes associated with severe forms of TBE as well as biological pathways through which the identified variants may influence the severity of the disease. RESULTS: Whole-exome sequencing data analysis was performed on 22 Russian patients with severe forms of TBE and 17 Russian individuals from the control group. We identified 2407 candidate genes harboring rare, potentially pathogenic variants in exomes of patients with TBE and not containing any rare, potentially pathogenic variants in exomes of individuals from the control group. According to DAVID tool, this set of 2407 genes was enriched with genes involved in extracellular matrix proteoglycans pathway and genes encoding proteins located at the cell periphery. A total of 154 genes/proteins from these functional groups have been shown to be involved in protein-protein interactions (PPIs) with the known candidate genes/proteins extracted from TBEVHostDB database. By ranking these genes according to the number of rare harmful minor alleles, we identified two genes (MSR1 and LMO7), harboring five minor alleles, and three genes (FLNA, PALLD, PKD1) harboring four minor alleles. When considering genes harboring genetic variants associated with severe forms of TBE at the suggestive P-value < 0.01, 46 genes containing harmful variants were identified. Out of these 46 genes, eight (MAP4, WDFY4, ACTRT2, KLHL25, MAP2K3, MBD1, OR10J1, and OR2T34) were additionally found among genes containing rare pathogenic variants identified in patients with TBE; and five genes (WDFY4, ALK, MAP4, BNIPL, EPPK1) were found to encode proteins that are involved in PPIs with proteins encoded by genes from TBEVHostDB. Three genes out of five (MAP4, EPPK1, ALK) were found to encode proteins located at cell periphery. CONCLUSIONS: Whole-exome sequencing followed by systems biology approach enabled to identify eight candidate genes (MAP4, WDFY4, ACTRT2, KLHL25, MAP2K3, MBD1, OR10J1, and OR2T34) that can potentially determine predisposition to severe forms of TBE. Analyses of the genetic risk factors for severe forms of TBE revealed a significant enrichment with genes controlling extracellular matrix proteoglycans pathway as well as genes encoding components of cell periphery.

A matrix metalloproteinase 9 (MMP9) gene single nucleotide polymorphism is associated with predisposition to tick-borne encephalitis virus-induced severe central nervous system disease.

The progression of infectious diseases depends on causative agents, the environment and the host's genetic susceptibility. To date, human genetic susceptibility to tick-borne encephalitis (TBE) virus-induced disease has not been sufficiently studied. We have combined whole-exome sequencing with a candidate gene approach to identify genes that are involved in the development of predisposition to TBE in a Russian population. Initially, six exomes from TBE patients with severe central nervous system (CNS) disease and seven exomes from control individuals were sequenced. Despite the small sample size, two nonsynonymous single nucleotide polymorphisms (SNPs) were significantly associated with TBE virus-induced severe CNS disease. One of these SNPs is rs6558394 (G/A, Pro422Leu) in the scribbled planar cell polarity protein (SCRIB) gene and the other SNP is rs17576 (A/G, Gln279Arg) in the matrix metalloproteinase 9 (MMP9) gene. Subsequently, these SNPs were genotyped in DNA samples of 150 non-immunized TBE patients with different clinical forms of the disease from two cities and 228 control randomly selected samples from the same populations. There were no statistically significant differences in genotype and allele frequencies between the case and control groups for rs6558394. However, the frequency of the rs17576 G allele was significantly higher in TBE patients with severe CNS diseases such as meningo-encephalitis (43.5%) when compared with TBE patients with milder meningitis (26.3%; P = 0.01), as well as with the population control group (32.5%; P = 0.042). The results suggest that the MMP9 gene may affect genetic predisposition to TBE in a Russian population.

Effective transcription factor binding site prediction using a combination of optimization, a genetic algorithm and discriminant analysis to capture distant interactions.

BACKGROUND: Reliable transcription factor binding site (TFBS) prediction methods are essential for computer annotation of large amount of genome sequence data. However, current methods to predict TFBSs are hampered by the high false-positive rates that occur when only sequence conservation at the core binding-sites is considered. RESULTS: To improve this situation, we have quantified the performance of several Position Weight Matrix (PWM) algorithms, using exhaustive approaches to find their optimal length and position. We applied these approaches to bio-medically important TFBSs involved in the regulation of cell growth and proliferation as well as in inflammatory, immune, and antiviral responses (NF-kappaB, ISGF3, IRF1, STAT1), obesity and lipid metabolism (PPAR, SREBP, HNF4), regulation of the steroidogenic (SF-1) and cell cycle (E2F) genes expression. We have also gained extra specificity using a method, entitled SiteGA, which takes into account structural interactions within TFBS core and flanking regions, using a genetic algorithm (GA) with a discriminant function of locally positioned dinucleotide (LPD) frequencies. To ensure a higher confidence in our approach, we applied resampling-jackknife and bootstrap tests for the comparison, it appears that, optimized PWM and SiteGA have shown similar recognition performances. Then we applied SiteGA and optimized PWMs (both separately and together) to sequences in the Eukaryotic Promoter Database (EPD). The resulting SiteGA recognition models can now be used to search sequences for BSs using the web tool, SiteGA. Analysis of dependencies between close and distant LPDs revealed by SiteGA models has shown that the most significant correlations are between close LPDs, and are generally located in the core (footprint) region. A greater number of less significant correlations are mainly between distant LPDs, which spanned both core and flanking regions. When SiteGA and optimized PWM models were applied together, this substantially reduced false positives at least at higher stringencies. CONCLUSION: Based on this analysis, SiteGA adds substantial specificity even to optimized PWMs and may be considered for large-scale genome analysis. It adds to the range of techniques available for TFBS prediction, and EPD analysis has led to a list of genes which appear to be regulated by the above TFs.

Human Genes Encoding Transcription Factors and Chromatin-Modifying Proteins Have Low Levels of Promoter Polymorphism: A Study of 1000 Genomes Project Data.

The expression level of each gene is controlled by its regulatory regions, which determine the precise regulation in a tissue-specific manner, according to the developmental stage of the body and the necessity of a response to external stimuli. Nucleotide substitutions in regulatory gene regions may modify the affinity of transcription factors to their specific DNA binding sites, affecting the transcription rates of genes. In our previous research, we found that genes controlling the sensory perception of smell and genes involved in antigen processing and presentation were overrepresented significantly among genes with high SNP contents in their promoter regions. The goal of our study was to reveal functional features of human genes containing extremely small numbers of SNPs in promoter regions. Two functional groups were found to be overrepresented among genes whose promoters did not contain SNPs: (1) genes involved in gene-specific transcription and (2) genes controlling chromatin organization. We revealed that the 5'-regulatory regions of genes encoding transcription factors and chromatin-modifying proteins were characterized by reduced genetic variability. One important exception from this rule refers to genes encoding transcription factors with zinc-coordinating DNA-binding domains (DBDs), which underwent extensive expansion in vertebrates, particularly, in primate evolution. Hence, we obtained new evidence for evolutionary forces shaping variability in 5'-regulatory regions of genes.

Genetic basis of olfactory cognition: extremely high level of DNA sequence polymorphism in promoter regions of the human olfactory receptor genes revealed using the 1000 Genomes Project dataset.

The molecular mechanism of olfactory cognition is very complicated. Olfactory cognition is initiated by olfactory receptor proteins (odorant receptors), which are activated by olfactory stimuli (ligands). Olfactory receptors are the initial player in the signal transduction cascade producing a nerve impulse, which is transmitted to the brain. The sensitivity to a particular ligand depends on the expression level of multiple proteins involved in the process of olfactory cognition: olfactory receptor proteins, proteins that participate in signal transduction cascade, etc. The expression level of each gene is controlled by its regulatory regions, and especially, by the promoter [a region of DNA about 100-1000 base pairs long located upstream of the transcription start site (TSS)]. We analyzed single nucleotide polymorphisms using human whole-genome data from the 1000 Genomes Project and revealed an extremely high level of single nucleotide polymorphisms in promoter regions of olfactory receptor genes and HLA genes. We hypothesized that the high level of polymorphisms in olfactory receptor promoters was responsible for the diversity in regulatory mechanisms controlling the expression levels of olfactory receptor proteins. Such diversity of regulatory mechanisms may cause the great variability of olfactory cognition of numerous environmental olfactory stimuli perceived by human beings (air pollutants, human body odors, odors in culinary etc.). In turn, this variability may provide a wide range of emotional and behavioral reactions related to the vast variety of olfactory stimuli.

Combined experimental and computational approaches to study the regulatory elements in eukaryotic genes.

The recognition of transcription factor binding sites (TFBSs) is the first step on the way to deciphering the DNA regulatory code. There is a large variety of experimental approaches providing information on TFBS location in genomic sequences. Many computational approaches to TFBS recognition based on the experimental data obtained are available, each having its own advantages and shortcomings. This article provides short review of approaches to computational recognition of TFBS in genomic sequences and methods of experimental verification of predicted sites. We also present a case study of the interplay between experimental and theoretical approaches to the successful prediction of Steroidogenic Factor 1 (SF1).

GeneNet database: description and modeling of gene networks.

Almost all cellular processes in an organism are controlled by gene networks. Here we report on the analysis of gene networks functioning using two associated methods - data accumulation in GeneNet system and generalized chemical kinetic method for mathematical simulation of gene network functional dynamics. The technology of the usage of these methods is shown on the example of the gene network of macrophage activation.