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Strategies for Network GWAS Evaluated Using Classroom Crowd Science.

Samson H Fong1, Daniel E Carlin2, Kivilcim Ozturk3

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Biological networks enhance genome-wide association studies (GWAS) for disease gene discovery. A classroom competition involving graduate students yielded creative solutions for network GWAS algorithms, demonstrating crowd science as a research and teaching tool.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Systems Biology

Background:

  • Biological networks are crucial for identifying disease-related genes in genome-wide association studies (GWAS).
  • Exploring and refining network-based GWAS methodologies is essential for advancing genetic research.

Purpose of the Study:

  • To investigate and improve network GWAS algorithms.
  • To assess the utility of classroom crowd science for biological research and education.

Main Methods:

  • A four-week classroom competition was designed for graduate students in a Network Biology and Biomedicine course.
  • Students were tasked with exploring and enhancing existing network GWAS methods.

Main Results:

  • Students developed numerous innovative solutions for network GWAS algorithms.
  • The study highlights the effectiveness of crowd science in a pedagogical setting.

Conclusions:

  • Classroom crowd science can be a valuable tool for both research and education in bioinformatics.
  • Creative solutions for network GWAS can emerge from collaborative, competitive learning environments.