George Aristidis Elder
Project title: Explaining large-scale phosphoproteomics data
Summary: The diverse and highly complex nature of modern biological research produces a high volume of data. Within it lie unexpected results, which can reveal new knowledge and/or lead to further testable hypotheses. However, these outcomes might be inherently wrong, resulting from gaps in researchers’ prior knowledge, poor choice of statistical analysis, or simply due to experimental error. Thus, there is unprecedented need to develop tools and methodologies to explain and rationalise these results.
Specifically, the aim of this PhD project is to develop novel logic-based algorithms that overcome the limitations of existing tools used for analysis. Ultimately, the most challenging aspect of this work will be to develop an automated hypotheses generation and validation algorithm. This will be able to employ abductive reasoning in combination with scientific knowledge and expertise to logically analyse not only datasets which suffer from the issues mentioned above but others as well. The resulting hypotheses can then be validated entirely in silico based on information garnered from other databases. If this yields interesting and novel results these can ultimately be tested by carrying out the relevant physical experiments manually.