Fall 2024 Course Spotlight
Boston University’s Faculty of Computing & 数据科学 is pleased to highlight a sampling of Fall 2024 semester courses. Learn about some of the upcoming computing and data sciences courses, the faculty leading the charge, and discover the inspiration behind each of these courses.
CDS DS 526: Critical Reading in Biological Data Science
Brian Cleary
Assistant Professor of Computing & 数据科学 + Biology + Biomedical Engineering
"With rapid the progress in access to data and development of sophisticated techniques for biological data science, it has become imperative that scientists and engineers learn to critically evaluate new forms of biological research. This course, which involves deep-dives into a small number of papers and their associated data, is designed to meet that need while also teaching students to identify how ideology and worldview shape biological research," — Professor Cleary.
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Pre-Requisite: Experience with computational biology.
This course satisfies the In the Field Track.
CDS DS 596: Introduction to Bioinformatics
Paweł Przytycki
Assistant Professor of Computing & 数据科学
"Did you know that the number of sequenced human genomes is growing faster than Moore's law? With the quantity of biological data outpacing our ability to build faster computers, there is an enormous need for algorithms capable of making sense of it all. In this course, which is designed for undergraduate students with no background in biology, students will learn the fundamental algorithms that form the backbone of modern bioinformatics," — Professor Przytycki.
About the Course: Introduction to Bioinformatics. Bioinformatics is an interdisciplinary filed combing data science, computing, algorithms, and programming with biology. This course teaches the fundamental algorithms that form the backbone of modern bioinformatics as well as their implementations and applications to data. Topics covered include genome assembly, sequence alignment, phylogenetic trees, gene regulation, and large-scale genomics data as well as associated computational methods including graph algorithms, dynamic programming, combinatorial pattern matching, tree algorithms, and machine learning. Familiarity with algorithms and python is expected. No background in biology required.
Undergraduate Prerequisites: CDS DS 210 and 320. This course satisfies:
- Analytics in the field
- Algorithmics in the field
Have questions about the undergraduate program? Email cds-advising@bu.edu. Access additional advising resources here.