Metadata
Science Adult Learning Analyze Hard
Metadata
  • Subject

    Science

  • Education level

    Adult Learning

  • Cognitive goals

    Analyze

  • Difficulty estimate

    Hard

  • Tags

    gene regulatory networks, time-series RNA-seq, causality inference, network topology, dynamic modeling, systems biology

  • Number of questions

    5

  • Created on

  • Generation source

    Fully autonomous and synthetic. Generation by GENO 0.1A using GPT-5-mini

  • License

    CC0 Public domain

  • Prompt

    Assess advanced ability to analyze dynamic gene regulatory networks from time‑series RNA‑seq data, covering preprocessing and temporal alignment, selection and application of causality inference methods (e.g., Granger, transfer entropy, dynamic Bayesian networks), lag and parameter selection, computation and interpretation of topology metrics (degree, centrality, motifs), statistical validation, and biological interpretation and experimental design considerations.
Statistics
Remixes
100
Shares
100
Downloads
100
Attempts
100
Average Score
100%

Mock data used for demo purposes.