ReviewNature reviews. Genetics2015
Methods of integrating data to uncover genotype-phenotype interactions.
Review in Nature reviews. Genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 509 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
509 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Gene signature discovery and systematic validation across diverse clinical cohorts for TB prognosis and response to treatment.PLoS computational biology · 2023Pooled it
- Genetic kidney diseases: Decoding molecular taxonomies to drive precision nephrology and therapeutic innovation.Genes & diseases · 2027Review
- AI-based multimodal integration of genomics and electronic health records.Nature reviews. Genetics · 2026Review
- Target discovery and drug design in the era of artificial intelligence.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026Review
- Operationalizing Precision Medicine in Drug Development: Predictive Biomarkers, Companion Diagnostics, and Regulatory Pathways.Clinical pharmacology and therapeutics · 2026Review
- Reconstructing bovine disease trajectories through integrative multi-omics: molecular decision nodes, predictive biomarkers and precision intervention.Veterinary research communications · 2026Review
- Multi-omics integration of proteomics and metabolomics in pediatric health and disease.Communications medicine · 2026Review
- Research progress on genomic selection breeding technology for crops.Protoplasma · 2026Review
- Genome-phenome association prediction using weighted deep matrix factorization with a multisource graph attention network.Quantitative biology (Beijing, China) · 2026Article
- Size-Resolved Lipoprotein Fatty Acid Content as a Novel Nuclear Magnetic Resonance-Derived Trait Specifically Associates with Genetic Variants That Control Fatty Acid Metabolism.Journal of proteome research · 2026Article
- A Bioinformatics Analysis Based on Omics and Clinical Data for Graph-Based Patient Stratification in Hepatocellular Carcinoma.Biology · 2026Article
- Article
- IMMUNIA: A Reasoning-Centered Framework for Immunoregulatory Surfaceome Discovery.ACS pharmacology & translational science · 2026Article
- Historical Perspectives, Classification and Diagnostic Approaches of Inborn Errors of Metabolism: A Systematic Review and Meta-Analysis.Metabolites · 2026Review
- Machine Learning and Artificial Intelligence in Nutrition Research: Analytical Methods, Applications, and Key Considerations.The Journal of nutrition · 2026Review
- miRNA-lncRNA Cross-Regulation Landscape in Cancer: From Molecular Mechanisms to Therapeutic and Diagnostic Applications.Cancers · 2026Review
- Decoding causal m6A: a bioinformatics roadmap for psychiatric disorders.Briefings in bioinformatics · 2026Review
- Assessing current capabilities for incorporating lipidomics in multiomics data integration.Briefings in bioinformatics · 2026Review
- Integrative Multi-Omics and Machine Learning Analysis Identifies Therapeutic Targets and Drug Repurposing Candidates for Alzheimer's Disease.Biomedicines · 2026Article
- Integrative Multi-Omics Analysis and Computational Modeling Identifying Shared Inflammatory Pathways and JAK Inhibitor Targets in PG and IBD.International journal of molecular sciences · 2026Article
449 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Recent technological advances have expanded the breadth of available omic data, from whole-genome sequencing data, to extensive transcriptomic, methylomic and metabolomic data. A key goal of analyses of these data is the identification of effective models that predict phenotypic traits and outcomes, elucidating important biomarkers and generating important insights into the genetic underpinnings of the heritability of complex traits. There is still a need for powerful and advanced analysis strategies to fully harness the utility of these comprehensive high-throughput data, identifying true associations and reducing the number of false associations. In this Review, we explore the emerging approaches for data integration - including meta-dimensional and multi-staged analyses - which aim to deepen our understanding of the role of genetics and genomics in complex outcomes. With the use and further development of these approaches, an improved understanding of the relationship between genomic variation and human phenotypes may be revealed.
Indexed as
Identifiers
25582081What OpenQuestion holds
Registered trials
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.