Stony Brook University 3 credits BMI
This course will provide students with an integrative computational toolbox at the intersection between Biomedical and Quantitative Sciences. Students will develop storage, analytic, and interpretive methods to optimize the transformation of large biomedical and genomic datasets, into proactive, predictive, preventive, and participatory health information. Applying a working knowledge of Computational Statistics in a Biomedical/Biomolecular context, students will gain the ability integrate those Computational Tools and Big Data resources in the Biomedical research enterprise as well as in the clinical workflow. Accordingly, this course will familiarize the participants with the data processing methodologies associated with a range of biological signals that spans from Biological sequences to Histology images, and from mining medical records to Genome Wide Association Studies (GWAS) and gene prioritization. 3 credits Grading Letter graded (A, A-, B+, etc.)
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