Article

OmicFormer: a statistical priors-informed transformer for accurate and generalizable omics prediction of diseases and complex traits

2026-07-10

Abstract excerpt

Precision medicine faces a critical challenge in translating high-dimensional omics data into robust disease predictions across diverse populations. Current approaches often fail under distribution shifts, partly due to their inability to encode complex biological feature dependencies. We present OmicFormer, a Transformer-based architecture that embeds two complementary statistical priors, i.e., feature-label asso...

Topics

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

Identifiers and source

Literature Corpus work: 77df86e7-102c-5a5a-9640-098dab717176
DOI: 10.64898/2026.07.06.26357359

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

OmicFormer: a statistical priors-informed transformer for accurate and generalizable omics prediction of diseases and complex traitsDOI 10.64898/2026.07.06.26357359Read

OmicFormer: a statistical priors–informed transformer for accurate and generalizable omics prediction of diseases and complex traitsSemantic proximity Read

A Multimodal Foundation Model for Discovering Genetic Associations with Brain Imaging PhenotypesSemantic proximity Read

MOT: a Multi-Omics Transformer for multiclass classification tumour types predictionsSemantic proximity Read

ProMeta: A meta-learning framework for robust disease diagnosis and prediction from plasma proteomicsSemantic proximity Read

Genomic Feature Transformation for Multi-Omics Integration in Clinical Prediction ModelsSemantic proximity Read

Genetic decoding reveals druggable biology implicitly learned by a medical-history foundation modelSemantic proximity Read

Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data.Semantic proximity Read

MOT: a Multi-Omics Transformer for multiclass classification tumour types predictionsSemantic proximity Read

An integrated Bayesian framework for multi-omics prediction and classificationSemantic proximity Read

Varmole: A biologically drop-connect deep neural network model for prioritizing disease risk variants and genesSemantic proximity Read

PheCode-guided multi-modal topic modeling of electronic health records improves disease incidence prediction and GWAS discovery from UK Biobank.Semantic proximity Read

Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics dataSemantic proximity Read