Bioinformatics method development for analysis of flow cytometric data from prostate cancer patients
Multicolour Flow cytometry (MFC) can identify and characterise cellular populations and subpopulations from blood based on up to 12 selected markers. However, the gating analysis applied to MFC data is subjective and only characterises populations in two dimensions at any one time. This fails to identify many potentially important cellular and sub-populations. Bioinformatic analysis is rarely applied to this problem but is suited to analyse multidimensional data.
The aims are to:
- Develop ANN based bioinformatics techniques for MFC data.
- Characterise in multiple dimensions for cellular subpopulations relating to clinical features of prostate cancer patients Identify markers relating to these populations.
Applications can be accepted from UK/EU and also International students. The minimum English language proficiency requirement for candidates who have not undertaken a higher degree at a UK HE institution is IELTS 6.5 or TOEFL 560/iBT 94 - 95.