Biological Data Sciences (BDS)

BDS 211. USE AND ABUSE OF DATA: CRITICAL THINKING IN SCIENCE. (3 Credits)

Critically examine how data analysis can support legitimate conclusions from biological datasets and also how deceptive visualizations, misleading comparisons, and spurious reasoning can lead to false conclusions. Analyze data to break down the logical flow of an argument and identify key assumptions, even when they are not stated explicitly.

Prerequisites: (MTH 251 (may be taken concurrently) with C- or better or MTH 251H (may be taken concurrently) with C- or better) or MTH 227 with C- or better or MTH 241 with C- or better or MTH 245 with C- or better

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 411. *ANALYSIS OF BIOLOGICAL DATA: CASE STUDIES. (3 Credits)

Case studies; synthesize previously acquired knowledge and skills in biology, mathematics, statistics, and computer science to implement, in writing, an analysis strategy. (Writing Intensive Course)

Attributes: CWIC – Core, Skills, WIC

Prerequisites: ((BI 311 with C- or better or BI 311H with C- or better) or (BB 314 with C- or better or BB 314H with C- or better) or MB 310 with C- or better) and ((MTH 252 with C- or better or MTH 252H with C- or better) or MTH 228 with C- or better) and CS 261 [C-] and (ST 352 [C-] or ST 412 [C-])

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 492. CAPSTONE PROJECTS IN BIOLOGICAL DATA SCIENCE II. (3 Credits)

Quantitative skills and biological thinking will be used to analyze and draw conclusions from biological datasets retrieved in BDS 412. This is a synthesis course that draws skills in mathematics, statistics, computer science, and biology, in which the students will process their curated datasets and draw conclusions.

Prerequisites: BDS 491 with C- or better

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

This course is repeatable for 99 credits.