A framework for automated gene selection in genomic applications.

L Lazo de la VegaW YuK MachiniC A Austin-TseL HaoC L Blout ZawatskyH Mason-SuaresR C GreenH L RehmMatthew S Lebo

Published in: Genetics in medicine : official journal of the American College of Medical Genetics (2021)

Our approach efficiently creates highly sensitive gene lists for genomic applications, while remaining dynamic and updatable, enabling time savings in genomic applications.

Keyphrases

copy number
genome wide
machine learning
genome wide identification
high throughput
deep learning
gene expression
fluorescent probe
high resolution
molecularly imprinted
transcription factor
living cells