The Biostatistics and Bioinformatics Core Facility provides expert guidance and support for processing, preparing, and analyzing a wide range of biological, clinical, and pathological data. The facility utilizes established, standardized workflows for processing next-generation sequencing data, including pipeline solutions from the nf-core community project, ensuring efficient and reproducible handling of biomaterial data. Services include experiment planning (e.g., sample size estimation), selection of appropriate technical methodologies, and advanced biostatistical and bioinformatics analyses. The team is skilled in managing high-dimensional and heterogeneous datasets using scripting languages (e.g., R, Python) and scalable computing resources. Analytical approaches encompass supervised methods (e.g., regression, classification, survival analysis) and unsupervised techniques (e.g., clustering, dimensionality reduction), along with deep learning methods (e.g., convolutional neural networks) for image analysis, including tasks such as feature extraction, segmentation, and classification in medical and biological imaging.
