Repositorio Institucional de la Universidad de Granada
metadata only
Multi-omics data integration using machine learning to understand the molecular mechanisms of insulin resistance in children with obesity during pubertal development
Childhood obesity is a major global health challenge and a key driver of early metabolic dysfunction. Among its cardiometabolic complications, insulin resistance (IR) emerges during paediatric life and frequently worsens across puberty, a developmental window characterised by profound hormonal,
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Genetic determinants of childhood blood pressure and heart rate in relation to adult health outcomes: the consortium of childhood blood pressure#1065977
- Impact of Comprehensive Intervention on the Cardiometabolic Risk in Children With Central Obesity (IGENOI)Obesity#1171538
- Supplemental material for NHANES Dataset#1042304
- Impaired Adipogenesis in Insulin Resistance: Pilot Clinical and In Vitro Studies#904871
- Using Machine Learning to Investigate Predictors of Fasting Blood Glucose: Insights into Circadian Timing and Age Interactions#1116717
Record · ID 824062
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive