chronic and acute lung diseases, autoimmune and autoinflammatory diseases, etc. They are often classfied and described by common symptoms, e.g. Thus, causes and pathomechanisms of these diseases are often difficult to uniquely describe and classify. Pathway deregulation landscapes in complex diseasesĬomplex human disea ses are often described concerted changes in various aspects of cellular life: from mutations to epigenetic changes and associated changes in transcriptome. The signal flow is visualized within the Cytoscape environment and a report file is generated for quantitative analysis. – Algorithms for handling of feedback loops. – Algorithms for processing multiple signals entering or leaving a node. – Mathematical funtions can to edges of different types for processing source to target signal transfer. PSFC allows for using custom algorithms and mathematical functions to characterize the signal flow within a pathway graph. PSFC: Pathway signal flow calculator app for cytoscape. Provides functionality for tuning the pathways based on tissue-specific gene expression and protein-protein interactions. Applied automati corrections for missing nodes and edges. Imports KEGG pathways into Matlab by creating a biograph object, and allows to edit nodes and edges and save the edited graphs for further analysis.ĬyKE GGParser: a Cytoscape app for parsing, editing and tuninig of KEGG pathway maps. Downloads and imports KEGG pathways into Cytoscape. KEGGParser: a tool for parsing and editing KEGG pathway graphs in Matlab.
CYTOSCAPE PATHWAY FLUX SOFTWARE
We have developed software packages for R, Matlab and Cytoscape (see the Software list) to allow for pathway parsing, editing, tuning and applying PSF algorithms on pathway topologies. Thus, PSF can be an indicator of pathway activity state. Assessment of changes in pathway activity is of major interest for identification of processes involved in the formation of certain phenotypes (healthy and diseased states), and assessment of cell response to drugs and other stimuli. Pathway Signal Flow (PSF), or perturbation, is the flux generated by propagation of the signal starting from input nodes, flowing through intermediate nodes in branches and accumulating at sink nodes. We than apply algorithms for pathway signal flow calculation. In contrast to gene-centered analysis, this approach accounts for the interactions between gene products and provides biological significance of the observed disturbances. For this we use gene expression data and pathway topology information obtained from publicly available databases, such KEGG, and manually edited or curated ones. We try to understand how the activity state of the pathways changes during disease development. a ligand binding to a receptor) and result in realization of certain target processes (e.g. Genetic analysis of SARS-CoV-2 in Armeniaĭrug repositioning for COVID-19 with multimodal biological dataĬomputational analysis of disease pathomechanisms Pathway-centered analysis of high-throughput dataĬell signaling pathways are sets of directed interactions between biological molecules, that are initiated by a particular signal (e.g. Telomere length calculation from NGS dataĪssociation of telomere length dynamics with transcriptome and epigenome Pathway deregulation landscapes in complex diseases Pathway-centered analysis of high-throughput data Current research focus of our group involves computational analysis of disease pathomechanisms, telomere bioinformatics and regulation of alternative splicing. This page highlights the main research directions, omitting the old, as well as the very new ones.Ĭomputational analysis of disease pathomechanisms Since 2011, we have focused on a variety of research topics and directions, such as protein structural modeling, gene ontology analysis, etc.
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