Article

RNAcompare: Integrating machine learning algorithms to unveil the similarities of phenotypes based on patients’ clinical, multi-omics using Rheumatoid Arthritis and Heart Failure as Case Studies

2025-04-08

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Background</h4> Gene expression analysis is crucial for understanding the biological mechanisms underlying patient subgroup differences. However, most existing studies focus primarily on transcriptomic data while neglecting the integration of clinical heterogeneity. Although batch correction methods are commonly used, challenges remain when integrating data across different tissues, omics l...

Topics

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

Identifiers and source

Literature Corpus work: 724c3ad6-bb12-5c9f-bf12-e388e64452cc
DOI: 10.1101/2025.04.02.646760

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

RNAcompare: Integrating machine learning algorithms to unveil the similarities of phenotypes based on patients’ clinical, multi-omics using Rheumatoid Arthritis and Heart Failure as Case StudiesDOI 10.1101/2025.04.02.646760Read

RNAchat: Integrating machine learning algorithms to identify metapathways based on clinical and multi-omics dataSemantic proximity Read

RNAcare: Integrating Clinical Data with Transcriptomic Evidence using Rheumatoid Arthritis as a Case StudySemantic proximity Read

Interpretable phenotype decoding from multi-condition sequencing data with ALPINESemantic proximity Read

Patient stratification reveals the molecular basis of disease comorbiditiesSemantic proximity Read

Bootstrap Evaluation of Association Matrices (BEAM) for Integrating Multiple Omics Profiles with Multiple OutcomesSemantic proximity Read

Multi-Omics-Based Sex Stratification Identifies Distinct High-Risk Phenotypes in HFpEFSemantic proximity Read

Combining explainable machine learning, demographic and multi-omic data to identify precision medicine strategies for inflammatory bowel diseaseSemantic proximity Read

Multi-modal integration of protein interactomes with genomic and molecular data discovers distinct RA endotypesSemantic proximity Read

Multivariate Random Forests for Cross-Modal Multi-Omics IntegrationSemantic proximity Read

EBEx: an Ensemble-Based Explainable Framework for Gene Calling in Heterogeneous DiseasesSemantic proximity Read

Explainable Artificial Intelligence for Cross-Dataset Generalizable Biomarker Discovery in Cardiovascular diseases (CVDs)Semantic proximity Read

Interpretable phenotype decoding from multicondition sequencing data with ALPINE.Semantic proximity Read