Article

Semi-supervised deep learning with graph neural network for cross-species regulatory sequence prediction

2022-05-19

Abstract excerpt

Genome-wide association studies have systematically identified thousands of single nucleotide polymorphisms (SNPs) associated with complex genetic diseases. However, the majority of those SNPs were found in non-coding genomic regions, preventing the understanding of the underlying causal mechanism. Predicting molecular processes based on the DNA sequence represents a promising approach to understand the role of th...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: c5aaa070-5fa9-5a2f-aab0-cd3d3a335c71
DOI: 10.1101/2022.05.17.492285

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Semi-supervised deep learning with graph neural network for cross-species regulatory sequence predictionDOI 10.1101/2022.05.17.492285Read

Semi-supervised learning improves regulatory sequence prediction with unlabeled sequencesSemantic proximity Read

Semi-supervised learning with pseudo-labeling compares favorably with large language models for regulatory sequence prediction.Semantic proximity Read

Cross-species regulatory sequence activity predictionSemantic proximity Read

Cross-species regulatory sequence activity prediction.Semantic proximity Read

Benchmarking DNA Sequence Models for Causal Regulatory Variant Prediction in Human GeneticsSemantic proximity Read

DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequencesSemantic proximity Read

Graph Neural Networks for Z-DNA prediction in GenomesSemantic proximity Read

The Nucleotide Transformer: Building and Evaluating Robust Foundation Models for Human GenomicsSemantic proximity Read

DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences.Semantic proximity Read

Learning functional conservation between pig and human to decipher evolutionary mechanisms underlying gene expression and complex traitSemantic proximity Read

SMG: self-supervised masked graph learning for cancer gene identification.Semantic proximity Read

MCNETSemantic proximity Read