Thomas Sauter
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Recent Grants
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Personalized risk stratification (iron overload): an integrative machine learning approach
Open Date: 2020-01-01
Close Date:
Grant: Close
Data-driven computational modelling and applications
Open Date: 2018-01-01
Close Date: 2025-01-01
Grant: Close
Systems medicine based patient stratification in cancer therapy
Open Date: 2018-01-01
Close Date:
Grant: Close
Computational Models and Algorithms for Predicting Cell Reprogramming Determinants with High Efficiency and High Fidelity
Open Date: 2017-01-01
Close Date: 2021-01-01
Grant: Close
Training in Cancer Biology: Focus on Tumour Escape Mechanisms
Open Date: 2016-01-01
Close Date: 2021-01-01
Articles (10)
Expanding the Disease Network of Glioblastoma Multiforme via Topological Analysis
Glioblastoma multiforme (GBM), a grade IV glioma, is a challenging disease for patients and clinicians, with an extremely poor prognosis. These tumours manifest a high molecular heterogeneity, with limited therapeutic options for patients. Since GBM is a rare disease, sufficient statistically strong evidence is often not available to explore the roles of lesser-known GBM proteins. We present a network-based approach using centrality measures to explore some key, topologically strategic proteins for the analysis of GBM. Since network-based analyses are sensitive to changes in network topology, we analysed nine different GBM networks, and show that small but well-curated networks consistently highlight a set of proteins, indicating their likely involvement in the disease. We propose 18 novel candidates which, based on differential expression, mutation analysis, and survival analysis, indicate that they may play a role in GBM progression. These should be investigated further for their functional roles in GBM, their clinical prognostic relevance, and their potential as therapeutic targets.
Year:
2023
Collaborators (3)
Daniela De Zio
Københavns Universitet
Daniel Kwaku Abankwa
-
Jun Pang
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