ArticleGenome biology2023
EvoAug: improving generalization and interpretability of genomic deep neural networks with evolution-inspired data augmentations.
Article in Genome biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 33 citations in OpenAlex.
- Balanced DNA interpolation improves learning of genetic distance-informed embeddings in plants.PLoS computational biology · 2026Article
- Toward generalizable and interpretable AI in regulatory genomics.Nature genetics · 2026Review
- Orthrus: toward evolutionary and functional RNA foundation models.Nature methods · 2026Article
- Designing DNA With Tunable Regulatory Activity Using Discrete Diffusion.bioRxiv : the preprint server for biology · 2026Article
- Multi-scale dissection, compaction and derivatization of mammalian developmental enhancers.bioRxiv : the preprint server for biology · 2026Article
- PoolParty: streamlined design of DNA sequence libraries in Python.bioRxiv : the preprint server for biology · 2026Article
- Distilling the Knowledge of Ensembles for Uncertainty-Aware Genomic Deep Learning.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Uncertainty-aware genomic deep learning with knowledge distillation.NPJ artificial intelligence · 2026Article
- Predicting gene expression from DNA sequence using deep learning models.Nature reviews. Genetics · 2025Review
- Orthrus: Towards Evolutionary and Functional RNA Foundation Models.bioRxiv : the preprint server for biology · 2025Article
- Innovative data augmentation strategy for deep learning on biological datasets with limited gene representations focused on chloroplast genomes.Scientific reports · 2025Article
- GENNUS: generative approaches for nucleotide sequences enhance mirtron classification.NAR genomics and bioinformatics · 2025Article
- Active learning of enhancers and silencers in the developing neural retina.Cell systems · 2025Article
- Language Modelling Techniques for Analysing the Impact of Human Genetic Variation.Bioinformatics and biology insights · 2025Review
- Uncertainty-aware genomic deep learning with knowledge distillation.bioRxiv : the preprint server for biology · 2024Article
- Semi-supervised learning with pseudo-labeling compares favorably with large language models for regulatory sequence prediction.Briefings in bioinformatics · 2024Article
- Genetic regulation of mScience China. Life sciences · 2024Review
- Assessing the reliability of point mutation as data augmentation for deep learning with genomic data.BMC bioinformatics · 2024Article
- Improving the performance of supervised deep learning for regulatory genomics using phylogenetic augmentation.Bioinformatics (Oxford, England) · 2024Article
- Deep learning in cancer genomics and histopathology.Genome medicine · 2024Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Deep neural networks (DNNs) hold promise for functional genomics prediction, but their generalization capability may be limited by the amount of available data. To address this, we propose EvoAug, a suite of evolution-inspired augmentations that enhance the training of genomic DNNs by increasing genetic variation. Random transformation of DNA sequences can potentially alter their function in unknown ways, so we employ a fine-tuning procedure using the original non-transformed data to preserve functional integrity. Our results demonstrate that EvoAug substantially improves the generalization and interpretability of established DNNs across prominent regulatory genomics prediction tasks, offering a robust solution for genomic DNNs.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.