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DATASCI 294B

Data Science for Computational Molecular Biology (DATASCI 194B)

UNITS:3
GRADING:Letter (ABCD/NP)
LEVEL:Graduate
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 294B: Data Science for Computational Molecular Biology (DATASCI 194B)

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 194B: Data Science for Computational Molecular Biology (DATASCI 294B)
  • 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
  • DATASCI 199W: Honors Capstone Thesis
  • DATASCI 200Q: Philosophical Foundations of Statistics (STATS 200Q)
  • DATASCI 211: Accelerating Research with Marlowe: Practical GPU Computing for Scientists
  • DATASCI 294C: Driving Innovation: Benchmarks, Competitions, and Challenge Problems in Machine Learning and Beyond (DATASCI 194C)
  • DATASCI 294L: Data Science and the Science of Learning (DATASCI 194L, EDUC 139, PSYCH 139)

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