Perturbations more reliably measure fine-scale network structure than coexpression.

Perturbations more reliably measure fine-scale network structure than coexpression.

<p><b>(A)</b> Distribution of perturbation effects and <b>(B)</b> coexpression values between pairs of genes that do or do not share an edge in a realistic synthetic GRN (both pairs of distributions have statistically distinguishable means; <i>p</i> < 10&...

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Bibliographic Details
Main Author:	Matthew Aguirre (9558032) (author)
Other Authors:	Jeffrey P. Spence (15317543) (author), Guy Sella (230321) (author), Jonathan K. Pritchard (8027465) (author)
Published:	2025
Subjects:	Genetics Molecular Biology Developmental Biology Infectious Diseases Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified world network theory consider future avenues interpret gene coexpression gene knockouts within better understand properties scale perturbation study like hierarchical structure unperturbed cells may gene regulation unperturbed states scale efforts key properties systematically describe remains challenging recent genome recapitulate features perturbation data new approach molecular perturbations modular organization efficient manner deeper analysis
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