Introduction

Last updated on 2024-01-04 | - + Edit this page

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Challenges in data-heavy biology -

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Challenges in data-heavy biology +


For example, consider biology.

This image shows the many different levels of data that biologists might work with. On the highest level, they work with organisms, shown in the image are a wasp, a tree, and a bacteria. On an intermediate level, they may collect raw data from these organisms. Shown in the image are a picture of dividing yeast cells, a western blot, and a floppy disk containing text data. On the final level, they will have visualisations of the raw data. Shown in the image are a picture of dividing cells with fluorescence at the boundary, a bar plot, and a cartoon of gene transcription.

Biologists study organisms, and have to deal with many kinds of data. In biology, as in other sciences:

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understand
  • Where do you even start?
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Good news: everyone has these problems! -

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Good news: everyone has these problems! +


  • Other people have thought about good practices and created good tools.
  • You don’t have to reinvent practices and tools.
  • You can learn to be “good enough” in scientific computing.
  • This is an ongoing process through your career.
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Principles: planning, modular organization, names, +

Principles: planning, modular organization, names, documentation -

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