Practicing Precision Medicine with Data Analysis course at Rutgers was designed with a new research-based approach, where students were introduced to the concepts of modern, basic and medical sciences. It has been grouped with theoretical discussions, basic and life science concepts, and computational skills. Case-studies discussed in this course include peer reviewed findings related toCOVID-19, Cardiovascular, Cancer, and other diseases.
Details are available in the course magazine:
Precision medicine aims to empower clinicians to predict the most appropriate course of action for patients with complex diseases,and improve routine medical and public health practice. However, practicing precision medicine is not straightforward, as significant efforts are required from the experts in multidisciplinary sciences. In this course, we have focused on discussing three important areas that heavily contribute to the development of precision medicine initiative: 1) understanding complexities of Electronic Healthcare Records; 2) bioinformatics applications for genomics data analysis; and 3) intelligent and integrative data analysis with machine learning algorithms. Active participation has helped students in learning about operational and academic medical systems, intelligently linking curated clinical data with computationally processed genomic data to identify functional variants among expressed genes, and investigating genotype and phenotype associations.
Course Title: Practicing Precision Medicine with Data Analysis
Semester: Spring 2022.
Course Number# 01:090:101 section 11.
Course URL: https://nbprovost.rutgers.edu/byrne-seminars/courses/practicing-precision-medicine-data-analysis
Related Publication:
– Abdelhalim, H., Berber, A., Lodi, M., Jain, R., Nair, A., Pappu, A., Patel, K., Venkat, V., Venkatesan, C., Wable, R., Dinatale, M., Fu, A., Iyer, V., Kalove, I., Kleyman, M., Koutsoutis, J., Menna, D., Paliwal, M., Patel, N., Patel, T., Rafique, Z., Samadi, R., Varadhan, R., Bolla, S., Vadapalli, S., & Ahmed, Z. (2022). Artificial Intelligence, Healthcare, Clinical-Genomics, and Pharmacogenomics Approaches in Precision Medicine. Section: Computational Genomics. Research Topic: Artificial Intelligence for Personalized and Predictive Genomics Data Analysis. Frontiers in Genetics. 13, 929736. PMID: 35873469. (Frontiers