CING Bioinformatics Department
Research Services
Issues of Complexity
31 employees
- Employees
- 31
CING Bioinformatics Department Overview
- Headquarters
- Issues of Complexity
- Website
- www.cing.ac.cy
- Industry
- Research Services
- Employees
- 31
- Founded
- 2016
- NAICS
-
Scientific Research and Development ServicesResearch and Development in the Physical, Engineering, and Life SciencesResearch and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
Keywords
Systems Bioinformatics
Biological Networks
Multiomics/Multimodal Data Integration
Single Cell Omics Analysis
Computational Drug Repurposing
Precision and Personalized Medicine
Computational Modeling
Computer-aided Molecular Diagnostics
Computational Insight into Disease and Disease Progression Mechanisms
Bioinformatics Exploring Life in Space - Astrobioinformatics
About CING Bioinformatics Department
The Bioinformatics Department at the Cyprus Institute of Neurology and Genetics (C-BIG) is a high-level interdisciplinary team that was established in 2016 to host the European Bioinformatics Research Area Chair in Cyprus with the support of the EU H2020 ERA Chair Grant BIORISE, for the period 2015-2020, and has since been transformed into a permanent department within the Cyprus Institute of Neurology and Genetics (CING). The Department's mission is to serve as a center of excellence in applied bioinformatics for early diagnosis, effective prognosis and drug discovery, contributing to the vision of precision and personalized medicine. This is achieved through cutting-edge bioinformatics research, postgraduate training and the ongoing development of bioinformatics methods and tools, either as services or as publicly available applications. The Department's research focuses on advanced computational diagnostics and therapeutics. We have a strong interest in applying advanced computational methods such as network analysis, machine learning/deep learning, multi-source data integration and modelling to biomedical problems to address issues of complexity, find hidden criticalities, monitor the systemic changes and ultimately approach with computational methods the most challenging questions related to human health, such as understanding the molecular mechanisms underlying disease and proposing candidate biomarkers/new or repurposed drugs for specific diseases or disease stages. (Informative Videos about the Department: https://youtu.be/mWZEwjv-RHs, https://www.youtube.com/watch?v=iFl4yJEDOHQ)
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