Fall 2024 Course Spotlight

Boston University’s Faculty of Computing & Data Sciences 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 & Data Sciences + 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.

About the Course: The goal of this course is to provide students with a framework, skills, and knowledge to critically evaluate research in biological data science. Biological research is rarely unequivocal in its findings; students will learn to systematically identify the claims advanced in research papers and evaluate whether each claim is established beyond a reasonable doubt by supporting evidence. We will examine papers that both meet and fail this test. In today's biology, to properly examine a paper in this way it is increasingly important to engage with the data provided as supporting evidence, and to critically examine the computational approach. Students will work with published data and computational tools. Further, students will learn to identify the ideology implicit in each paper, to understand how ideology shapes both the research questions and approach, and to imagine the same research under an alternative mindset. Classes will be split into lectures on background material for each paper and group discussions. Students will work in small groups to write a report on each paper. Each student will work on a final project to produce a critical review of a broader topic in the field.

Pre-Requisite: Experience with computational biology.

This course satisfies the In the Field Track.

Meeting Pattern:
Lecture M/W 12:20 - 2:05 pm
Discussion M 4:40 - 5:30 pm

CDS DS 596: Introduction to Bioinformatics

Paweł Przytycki

Assistant Professor of Computing & Data Sciences

"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
Meeting Pattern:
Lecture T/Th 11:00 am - 12:15pm
Discussion W 10:10 - 11am

Have questions about the undergraduate program? Email cds-advising@bu.edu. Access additional advising resources here