Multi-disciplinary Omics data science
The intersection of high-throughput omics technologies and computer power promises to change basic science and clinical practice in fundamental ways. To keep pace with the outpouring of omics data, we empower the next generation of scientists with skills that facilitate translating big data into applicable knowledge.
From a research perspective, our work is rooted in the basic sciences, and seeks to advance genomic medicine and make biopharmaceutical development more efficient. To achieve this, our approaches borrow strength across genomics, transcriptomics, ribosome profiling, proteomics, structural genomics, metabolomics and phenotype variability data. Integration of multi-omics data, such as these, has made it possible to bridge the genotype-phenotype gap and tie cellular processes together mechanistically.
From a mentoring perspective, our main teaching goal is to equip students with methodological training and hands-on practical experience required to bridge the gap between data and insight. We empower the next generation of scientists with the tools and concepts to manage and dissect the data they generate. Being able to tackle the proliferation of big biological data will be an asset to any biologist, physician scientist or computer scientist, regardless of career path or academic trajectory.