Login / Signup

Selecting genes for analysis using historically contingent progress.

Farhaan LalitAntony Merlin Jose
Published in: bioRxiv : the preprint server for biology (2024)
Progress in biology has generated numerous lists of genes that share some property. But, advancing from the initial implication of a set of genes in a process to understanding their roles in the process is slow and unsystematic. Here we use RNA silencing in C. elegans to illustrate a general approach for comparing lists of data accumulated by a field to prioritize genes for detailed study given limited resources. The partially subjective relationships between genes forged by both functional relatedness of the genes and biased progress in the field was captured as historical mutual information (HMI) and used as a quantitative measure for clustering genes. These clusters suggest regulatory links connecting RNA silencing with other processes like the cell cycle and identify understudied regulated genes that could be used to sense perturbation or mediate feedback inhibition.
Keyphrases
  • genome wide
  • bioinformatics analysis
  • cell cycle
  • genome wide identification
  • genome wide analysis
  • transcription factor
  • cell proliferation
  • single cell
  • health information