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Studying cancer with networks


We apply network-theoretic approach to study cancer related phenomena at the gene-scale level. Intracellular signalling networks comprise the information about interactions between numerous cellular components such as ligands, receptors, enzymes, RNA and DNA molecules, etc. Numerous intracellular signaling pathways formed by cascades of biochemical events in proteins triggered by extracellular cues dictate the cellular behavior and responses to the environment as well as define the cell’s phenotype. Disruptions of cellular signalling pathways caused for instance, by the genetic material alterations may lead to severe diseases such as cancer.
Our generic goal is to understand what is going wrong in oncogenic cells and to identify key proteins/genes and modules responsible for the malignant cellular behavior. We take a system-wide look at cellular processes, and in particular, we analyze topological, functional and dynamical features of the intracellular signalling networks representing those processes. We develop computational methods and tools to perform the analysis. Our aim is to obtain results with drug targets and therapeutic suggestions.
Our research is powered by Anduril workflow engine and vast set of Anduril workflow components. The real-world data import such as signalling networks, gene ontologies, drugs, etc, is carried by Moksiskaan database. We make Anduril workflow components and Anduril pipelines that automate our analysis and allow instant automatic updates of the results in case of the input data changes.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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