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Genome Features Spelled Out Using Models Trained With EvoAug Data Augmentation

In a paper appearing in Genome Biology, a Cold Spring Harbor Laboratory team describes a computational method known as EvoAug that is designed to boost the performance of deep neural network (DNN) models used to understand regulatory motifs and other genomic features with the help of genetic variation data and evolutionary insights. Starting with artificial DNA sequences resembling established sequences, the approach takes into account alterations that may crop up through evolution, the researchers write, adding that EvoAug training steps take changes that do or do not alter functional processes into account. The researchers found that EvoAug-trained models outperformed models trained on biological data alone when it came to evaluating cis-regulatory elements and transcription factor binding sites, for example. "Our findings support previous arguments for using evolution as a natural source of data augmentation," the authors write. They suggest EvoAug "will have broad utility in improving the efficacy of sequence-based DNNs for regulatory genomics."

The Scan

Open Pediatric Brain Tumor Atlas Team Introduces Genomic Data Collection, Analytical Tools

A study in Cell Genomics outlines open-source methods being used to analyze and translate whole-genome, exome, and RNA sequence data from the Pediatric Brain Tumor Atlas.

Neurological Outcomes Linked to Innate Immune Features After Cardiac Arrest

Researchers reporting in Med dig into immune features found a few hours after cardiac arrest that correspond with neurological outcomes.

Mouse Study Finds Circadian Rhythm-Related Gene Expression Changes Linked to Sleep Apnea

A paper in PLOS Biology reveals tissue-specific circadian rhythm and gene expression patterns in an intermittent hypoxia-based mouse model of obstructive sleep apnea.

Polygenic Risk Score to Predict Preeclampsia, Gestational Hypertension in Pregnant Women

Researchers in Nature Medicine provide new mechanistic insights into the development of hypertensive disorders of pregnancy, which may help develop therapeutics.