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prerequisites
intermediate Julia (data structures, loops, functions, composite types, plotting • data manipulation with DataFrames.jl) • basics of data science
skills learned
make simulations to compute “normal” LCS and identify outliers • determine how much is in common between each of the sequences from the outliers • draw conclusions from plots
Joris Limonier
1 week · 4-6 hours per week · BEGINNER
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In this liveProject, you’ll help find a cure for a (fictional) global pandemic by identifying the origin of the virus. Biologists have already narrowed the list of suspects down to three animal species. Longest Common Subsequences (LCS) can help you measure the similarity between two sequences. You'll use them to compare the animal sequences with the virus’ sequence. You'll get a sense of what percentage of the sequences should be common versus what is actually common between the sequences studied, then you'll be able to identify the virus’ origin based on your findings.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Joris Limonier
Joris Limonier has worked at the Unit of Research in Computer Science at the University of Luxembourg and has a strong background in Julia, Python for data science, LaTeX, and Swift. He’s earned degrees in mathematics, data science, and artificial intelligence. To share his passion for Julia, he creates Julia content including YouTube videos and open-source projects on GitHub.

prerequisites

The liveProject is for intermediate Julia programmers with experience plotting data. To begin these liveProjects you'll need to be familiar with the following:


TOOLS
  • Jupyter notebook or Notebooks in VS Code
  • Plots.jl for basic plotting
  • CSV.jl to import data from csv files
  • DataFrames.jl to exploit your data
TECHNIQUES
  • Basic mathematics and statistics (mathematical operations, logical reasoning)
  • Basics of programming (data structures, arrays, dictionaries, loops, functions)
  • Basics of data science (how to start with data, apply scientific reasoning and draw conclusions)

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