Biological Data Sciences (BDS)

BDS 311. COMPUTATIONAL APPROACHES FOR BIOLOGICAL DATA. (3 Credits)

Real-world biological datasets to implement fundamental concepts of efficient algorithm design. Synthesize previously acquired knowledge and skills in biology and computer science to analyze, implement, and apply algorithms that process biological datasets, including large-scale datasets.

Prerequisites: (BI 212 with C- or better or BI 212H with C- or better) and (MTH 252 [C-] or MTH 252H [C-]) and CS 261 [C-] and (BI 213 (may be taken concurrently) [C-] or BI 213H (may be taken concurrently) [C-]) and (ST 351 (may be taken concurrently) [C-] or ST 351H (may be taken concurrently) [C-])

BDS 406. SPECIAL PROJECTS. (1-99 Credits)

This course is repeatable for 99 credits.

BDS 491. CAPSTONE PROJECTS IN BIOLOGICAL DATA SCIENCE I. (3 Credits)

Quantitative skills and biological thinking will be used to analyze and draw conclusions from real-world biological datasets. Projects will be completed in the context of small groups. Draws on skills in mathematics, statistics, computer science, and biology.

Prerequisites: (ST 352 with C- or better or ST 412 with C- or better) and (CS 162 [C-] or BOT 476 [C-] or BB 485 [C-] or MTH 427 [C-])

BDS 599. SPECIAL TOPICS. (1-4 Credits)

This course is repeatable for 99 credits.