BioMedical Data and Image Analysis (BioMeDIA) Laboratory is led by Dr. Kathrin Tyryshkin, a biomedical data scientist, specializing in pattern recognition in high-dimensional biomedical and biological data. In the lab, we address the specific analytical challenges in basic and patient-oriented research by developing new computational and statistical techniques. We adapt and integrate powerful computational techniques for biomarker discovery and for building diagnostic and prognostic tools for medical conditions or diseases.

Students in our lab develop strong computational and data analysis skills required in biomedical data science. They also acquire working knowledge of high-priority issues in clinical medicine, genomics, and other biomedical fields, as well as awareness of the specific challenges that commonly arise when conducting productive, multidisciplinary clinical research.

What We Do

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Biomedical Data Science

Incorporating innovative methods found in computer science into algorithm design for more precise and informative biomedical data analysis. The research involves exploring complex and large genetic datasets for molecular patterns that may explain biological or clinical outcomes or suggest alternative treatments.

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Neuroendocrine Neoplasms

Seeking to identify the common molecular factors driving Neuroendocrine Neoplasm (NEN) progression across different disease sites. Currently, we are working on a new approach to disease classification of plasma samples using Fuzzy set theory. We are also exploring the biomarkers of neuroendocrine differentiation in other cancers.

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Multiplex IHC and IF Image Analysis

Researching biomedical image analysis techniques for developing biomarkers to predict grading and prognosis in medical pathology images. We are working on a comprehensive characterization of the pre-treatment tumour immune microenvironment using cutting-edge spatial proteomic and transcriptomic technologies.

Funding

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