Network Modeling for Omics Data (2019-2022)
As part of the Principles of Bioscience Omics course, I delivered a lecture on Network Modeling for Omics Data, focusing on the application of network science in systems biology. In this session, students were introduced to the conceptual and practical foundations of network-based approaches to analyzing high-dimensional omics datasets, including transcriptomics, proteomics, metabolomics, and lipidomics. We explored how networks can be used to model molecular interactions, integrate data across different omics platforms, and identify biologically meaningful patterns. The broader course provides a comprehensive overview of omics technologies and related bioinformatics tools. Students learn to design omics-based experiments, recognize methodological pitfalls, interpret multivariate omics data, and integrate information from various omics layers (e.g., genome, proteome, and metabolome). Special emphasis is placed on data interpretation and integration to prepare students for research in systems biology and personalized medicine.