NITPicker: selecting time points for follow-up experiments.

Published in: BMC bioinformatics (2019)

NITPicker performs well on diverse real-world datasets that would be relevant for varied biological applications, including designing follow-up experiments for longitudinal gene expression data, weather pattern changes over time, and growth curves.

Keyphrases

gene expression
dna methylation
electronic health record
big data
cross sectional
rna seq
machine learning
artificial intelligence