Svetlana Bulashevska

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We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive approaches. The model is capable to capture generic and structural properties of a network as emergent from local interdependencies and uses a limited number of parameters. Here, we consider one(More)
MOTIVATION High-throughput molecular genetics methods allow the collection of data about the expression of genes at different time points and under different conditions. The challenge is to infer gene regulatory interactions from these data and to get an insight into the mechanisms of genetic regulation. RESULTS We propose a model for genetic regulatory(More)
Urothelial cancers of the bladder (UC) comprise biologically heterogeneous group of tumors and display complex genetic alterations. Several genetic changes have been analyzed in detail and some of them are associated with the development and progression of UCs. Only a few studies, however, are focused on identifying the order in which the aberrations may(More)
In stroke, gene transcription plays a central role in processes such as neuroinflammation and neuroregeneration. To predict new transcriptional regulatory mechanisms in cerebral ischemia, we applied a computational approach combining two kinds of information: the results of a microarray analysis in a mouse model of stroke and in silico detection of(More)
Pancreatic ductal adenocarcinoma (PDAC) represents one of the deadliest cancers in the world. All-trans retinoic acid (ATRA) is the major physiologically active form of vitamin A, regulating expression of many genes. Disturbances of vitamin A metabolism are prevalent in some cancer cells. The main aim of this work was to investigate deeply the components of(More)
Endosomes constitute a central layer in the regulation of growth factor signaling. We applied flow cytometry, confocal microscopy and automated image quantification to define the role of Caveolin1 (Cav1) in epidermal growth factor (EGF) receptor (i) internalization and (ii) endosomal trafficking. Antisense-downregulation of Cav1 did not affect(More)
Background: Classification of human tumors into distinguishable entities is preferentially based on clinical, pathohistological, enzyme-based histochemical, immunohistochemical, and in some cases cytogenetic data. This classification system still provides classes containing tumors that show similarities but differ strongly in important aspects, e.g.(More)
The most fatal and prevalent form of malaria is caused by the bloodborne pathogen Plasmodium falciparum (henceforth P.f). Annually, approximately three million people died of malaria. Despite P.f devastating effect globally, the vast majority of its proteins have not been characterized experimentally. In this work, we provide computational insight that(More)