PhD Topics

1.     Development of bioinformatics methods for data integration from various diagnostic types in clinical oncology

Supervisor: Vojtěch ‚Bystrý, Ph.D.                                         

Consultant: Panagiotis Alexiou, Ph.D.

Annotation:
In the state of the art personalised therapy planning for oncology patients multiple examinations and laboratory tests are performed to get a thorough characterisation of a tumour. These examinations include all the various types of NGS based analysis such as fusion gene detection, mutation profiling, gene expression profiling, methylation profiling or micro RNA profiling, but also other pathological examination such as PET scan. Each of the analysis produces a huge and complex data that requires a specialised non-trivial computer processing to extract useful information. However, the real bioinformatics challenge is to integrate these data into a single model which would be able to make use of mutual information between different data sources and provide a comprehensive assessment of patients risks. The aim of the PhD study will be to develop such bioinformatics methods and machine learning models that will be capable of combining the various data into a single comprehensive result. The developed methods should be able to capture the 'expert knowledge', and close collaboration with clinical genetics and other medical professionals will be necessary.

Literature:

1. Barros-Silva, D. et al. (2018) ‘Profiling DNA Methylation Based on Next-Generation Sequencing Approaches: New Insights and Clinical Applications’, Genes, 9(9). doi: 10.3390/genes9090429.
2. Ramaswamy, V. et al. (2016) ‘Risk stratification of childhood medulloblastoma in the molecular era: the current consensus’, Acta neuropathologica. Springer, 131(6), pp. 821–831.
3. Bystry, V. et al. (2015) ‘ARResT/AssignSubsets: a novel application for robust subclassification of chronic lymphocytic leukemia based on B cell receptor IG stereotypy’, Bioinformatics , 31(23), pp.
4.  
5. Mertens, F. et al. (2015) ‘The emerging complexity of gene fusions in cancer’, Nature reviews. Cancer. nature.com, 15(6), pp. 371–381.
6. Santarius, T. et al. (2010) ‘A census of amplified and overexpressed human cancer genes’, Nature reviews. Cancer. nature.com, 10(1), pp.59–64.

Keywords: bioinformatics, next generation sequencing, data integration, oncology, personalized medicine