SYSPATHO

New Algorithms for Host Pathogen Systems Biology

 Partecipanti

Mappa

 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

 Obiettivo del progetto (Objective)

'SYSPATHO focuses on the development of novel and generally applicable mathematical methods and algorithms for systems biology. These methods and algorithms will be applied to study the complex interactions of hepatitis C virus (HCV), a human-pathogenic virus of high medical relevance, with its host at the systems level. Using a multidisciplinary, integrative approach, PATHOSYS will (a) develop methods to analyze and integrate a wide variety of data from wet lab experiments, databases and biological literature, (b) develop and apply machine learning tools to reconstruct and study intracellular interaction networks from experimental data, (c) develop new and improve existing algorithms and mathematical methods for bottom-up modelling, to fit models to data, and to analyze the dynamic behaviour of models (d) generate new experimental data to gain novel insights into hepatitis C virus host interactions, and (e) use the newly developed methods and data to model and analyze HCV-host interactions at the systems level. Guided by biological data, PATHOSYS focuses on the design of novel algorithms and mathematical methods for systems biology, with the aim to provide generally applicable tools to elucidate biological processes. Based on developed models and using systems analysis, PATHOSYS will elucidate virus host interactions of Hepatitis C virus at an unprecedented level. As a direct spin-off, models and analysis methods developed in PATHOSYS will lead to the identification of new candidate host cell target genes applicable for the design of novel anti-viral drugs against hepatitis C. Targeting of host cell factors will reduce the likelihood for the development of therapy resistance and increase the chance for broad-spectrum antivirals. Inclusion of two SME partners will ensure exploitation of results generated in PATHOSYS and their transfer into industrial and pharmaceutical applications, thus strengthening economy and health care system in Europe.'

Introduzione (Teaser)

Virus infections are complex biological processes, involving competition between the virus and the host cellular immune responses. In order to advance our understanding of virus infection, the Syspatho initiative is following a systems biology approach, aiming to identify therapeutically relevant targets.

Descrizione progetto (Article)

Hepatitis C is a major infectious disease caused by the hepatitis C virus (HCV) and affects more than 250 million people worldwide. HCV infects the liver and can persist over the years leading to chronic infection and serious liver diseases such as liver cirrhosis and cancer.

Currently, there is no vaccine available and standard treatment consists of antiviral and immunomodulating regimens. However, this therapy works only in some patients, necessitating the improved understanding of HCV infections to advance medical treatment.

The scientific objective of the EU-funded ?New algorithms for host pathogen systems biology? (Syspatho) project focuses on the development of novel mathematical methods and algorithms that could be applied to systems biology. As a paradigm, these methods are being applied to study the complex interactions of HCV, a human-pathogenic virus of high medical relevance, with its host.

Project partners are building their model by integrating and analysing data from wet lab experiments, databases and biological literature. The aim is to reconstruct and study intracellular interaction networks required by the virus.

Two different modelling approaches are being pursued: a bottom-up approach, where current knowledge about the signalling network is used, and a top-down approach, where model components from all possible molecular interactions are being selected. Combined with advanced experimental techniques such as live imaging of cells and molecular interaction determination, the Syspatho method will unveil the dynamics of HCV infection and host responses.

New data generated during the project have identified a number of proteins involved in the HCV innate immune network with special emphasis on the interferon (IFN) response. Integrating this data into the Syspatho mathematical model will be used to analyse for the determinants of chronic infection.

Overall, the Syspatho project deliverables will lead to the identification of new candidate host cell target genes applicable for the design of novel anti-viral drugs against hepatitis C. Apart from HCV, the Syspatho mathematical methods are of general applicability in the broader area of systems biology.