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Biomedical Image Analysis

Our current research focus lies in identifying biomarkers of brain disorders from neuroimaging data, which is an exciting and rapidly growing research area at the intersection of machine learning, biomedical engineering and neuroscience. Conventional approaches towards imaging biomarkers reduce the data dimensionality by averaging the image information to one or few variables of a-priori interest – for example, the volume of Hippocampus for Alzheimers diagnosis. However, such methods discard much information present in brain images. Instead, allowing machine learning algorithms to decide what is important and decipher the predictive pattern (sometimes called statistical biomarker) is projected to be beneficial. This leads to challenging and underconstrained machine learning problems where the data dimensionality is larger than the number of samples and advanced computational techniques are required to solve these problems. We develop these techniques and apply to them to large brain image databases to help neuroscientists to find imaging markers to different brain disorders.

Ina Pöhner (ina.pohner@uef.fi)

Early during my scientific career, I focused on studying protein-protein interactions by computational methods. During my PhD, I shifted my focus to protein-small molecule interactions and their modulation in the context of computer-aided drug design for neglected tropical diseases. As a passionate Linux-user and administrator, I moved on to dive into aspects of databases, data management and FAIR data (data that is Findable, Accessible, Interoperable, and Reusable).

My postdoctoral research at UEF finally connects all my expertise in data-intensive drug discovery projects, dedicated to anti-viral, anti-bacterial and anti-protozoal research. My projects involve, for example, semi-automated docking studies of several hundreds of targets and billion-scale virtual screening, where I utilize powerful combinations of computer-aided drug discovery and modeling techniques, programming, databases and machine-learning – and all that – naturally – penguin-powered.