The Hybrid Science
The potential of science in a data-driven world just keeps growing.
Data and analytics applied to science give rise to more rapid discoveries, swifter technological advances, and most importantly, more immediate impacts on the human condition.
Integrated knowledge from biological, computational and mathematical disciplines creates a unique professional perspective preparing graduates to play pivotal roles in today’s cutting-edge life sciences, biotechnology and pharmaceutical industries.
Students take classes in a range of disciplines including molecular biology, biochemistry, statistics, ethics, data mining and machine learning, giving them a competitive edge in the ever-expanding life sciences sector.
This is so much more than crunching numbers. It’s changing lives.
Introduces the concepts of probability and statistics used in bioinformatics applications, particularly the analysis of microarray data. Uses statistical computation using the open-source R program. Topics include maximum likelihood; Monte Carlo simulations; false discovery rate adjustment; nonparametric methods, including bootstrap and permutation tests; correlation, regression, ANOVA, and generalized linear models; preprocessing of microarray data and gene filtering; visualization of multivariate data; and machine-learning techniques, such as clustering, principal components analysis, support vector machine, neural networks, and regression tree.
Covers various aspects of data mining, including classification, prediction, ensemble methods, association rules, sequence mining, and cluster analysis. The class project involves hands-on practice of mining useful knowledge from a large data set.
Intended for those familiar with the basics of genetics, molecular and cellular biology, and biochemistry, all of which are required to appreciate the beauty, power, and importance of modern genomic approaches. Introduces the latest sequencing methods, array technology, genomic databases, whole genome analysis, functional genomics, and more.
- 6/1 International
- 8/15 Domestic
- 10/1 International
- 12/1 Domestic
- Bioinformatics and Chemoinformatics
- Bioinformatics Enterprise
- Data Analytics
5-9% expected national job growth for bioinformatic scientists by 2026 (US Department of Labor)
Real World Experience
Northeastern’s bioinformatics students benefit from Northeastern’s extensive network of industry partners in Boston, the San Francisco Bay Area, and around the globe. Masters degree students complete either a 4-8 month co-op work experience or participate in an industry-based independent project, providing an invaluable opportunity to gain professional training within the commercial sector.