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DATASCI 194B

Data Science for Computational Molecular Biology (DATASCI 294B)

UNITS:3
GRADING:Letter (ABCD/NP)
LEVEL:Undergrad
GER:—

Data science is a tool that can be applied to many domains. This course explores the application of computational techniques to analyze biological data at the molecular level. Students will learn tools for processing DNA, RNA, and protein sequences, as well as analyzing biomolecular structures. The course covers navigation of essential databases like NCBI GenBank, UniProt, and PDB, and introduces common algorithms used in molecular biology data analysis. Relevant topics include sequence alignment, structural analysis, and phylogenetics. Students will engage with real-world problems in bioinformatics and develop skills in data manipulation and interpretation. The course culminates in an independent research project, allowing students to apply their knowledge to a specific area of interest in computational molecular biology. Prerequisites: STATS DATASCI 200, DATASCI DATASCI 112 or STATS DATASCI 202, and ENGR 108 or MATH 104 or STATS DATASCI 203. Enrollment limited to senior undergraduates and graduate students. This course fulfills the capstone requirement for the Data Science BS and MCS.

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DATASCI 194B: Data Science for Computational Molecular Biology (DATASCI 294B)

3 units · Letter (ABCD/NP)

Data science is a tool that can be applied to many domains. This course explores the application of computational techniques to analyze biological data at the molecular level. Students will learn tools for processing DNA, RNA, and protein sequences, as well as analyzing biomolecular structures. The course covers navigation of essential databases like NCBI GenBank, UniProt, and PDB, and introduces common algorithms used in molecular biology data analysis. Relevant topics include sequence alignment, structural analysis, and phylogenetics. Students will engage with real-world problems in bioinformatics and develop skills in data manipulation and interpretation. The course culminates in an independent research project, allowing students to apply their knowledge to a specific area of interest in computational molecular biology. Prerequisites: STATS 200, DATASCI 112 or STATS 202, and ENGR 108 or MATH 104 or STATS 203. Enrollment limited to senior undergraduates and graduate students. This course fulfills the capstone requirement for the Data Science BS and MCS.

More DATASCI courses

  • DATASCI 156: Thinking and Making with Data (ENGLISH 156A)
  • DATASCI 161: Causality, Decision Making and Data Science (CS 171, ECON 115)
  • DATASCI 190: The Data Science Experience
  • DATASCI 192A: Data Science Practicum I
  • DATASCI 192B: Data Science Practicum II
  • DATASCI 193: Applied Artistic and Cultural Analysis
  • DATASCI 194C: Driving Innovation: Benchmarks, Competitions, and Challenge Problems in Machine Learning and Beyond (DATASCI 294C)
  • DATASCI 194L: Data Science and the Science of Learning (DATASCI 294L, EDUC 139, PSYCH 139)
  • DATASCI 194N: Data Science for Neuroscience (DATASCI 294N, PSYCH 294N)
  • DATASCI 196: Teaching Data Science
  • DATASCI 198: Practical Training
  • DATASCI 199: Independent Study

All DATASCI courses · All departments