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Data libraries - the missing element for modeling biological systems.

Anastasia Baryshnikova
Published in: The FEBS journal (2020)
The primary bottleneck in understanding and modeling biological systems is shifting from data collection to data analysis and integration. This process critically depends on data being available in an organized form, so that they can be accessed, understood, and reused by a broad community of scientists. A proven solution for organizing data is literature curation, which extracts, aggregates, and distributes findings from publications. Here, I describe the benefits of extending curation practices to datasets, especially those that are not deposited in centralized databases. I argue that dataset curation (or 'data librarianship' as I suggest we call it) will overcome many barriers in data visibility and reusability and make a unique contribution to integration and modeling.
Keyphrases
  • data analysis
  • electronic health record
  • big data
  • healthcare
  • systematic review
  • mental health
  • machine learning
  • artificial intelligence