Zinc Common Cold Meta-Analysis Evidence Table

Structured evidence table for Zinc Common Cold Meta-Analysis, generated from 2 reusable source documents in the Migaku knowledge base.

topicclaimevidence levelcitationsource
Zinc Common Cold Meta-AnalysisIn recent years, advancements in molecular biology techniques and the accumulation of extensive datasets have facilitated substantial progress in the identification, integration and analysis of QTLs associated with cold tolerance in rice [–].4Li Xiu-Jie (2026)Integrating Meta-QTL mapping and RNA-seq analysis identifies candidate genes for cold tolerance at rice seedling stage
Zinc Common Cold Meta-AnalysisThis integrative approach led to the identification of several QTLs associated with cold tolerance and BR signaling pathways.4Li Xiu-Jie (2026)Integrating Meta-QTL mapping and RNA-seq analysis identifies candidate genes for cold tolerance at rice seedling stage
Zinc Common Cold Meta-AnalysisIn this context, Meta-QTL analysis serves as a valuable tool for breeders by identifying genomic regions associated with specific traits through QTL data.4Li Xiu-Jie (2026)Integrating Meta-QTL mapping and RNA-seq analysis identifies candidate genes for cold tolerance at rice seedling stage
Zinc Common Cold Meta-AnalysisOryza sativa 1 2 3 4 5 6 9 10 11 Rice (L.) serves as a fundamental food source, with its production levels exerting a significant impact on international food security [].4Li Xiu-Jie (2026)Integrating Meta-QTL mapping and RNA-seq analysis identifies candidate genes for cold tolerance at rice seedling stage
Zinc Common Cold Meta-AnalysisBackground Effects of treatments on continuous outcomes are commonly estimated using the mean difference (in units of measurement) or the ratio of means (percentages), each providing a single average effect across the study population.4Hemilä H (2025)Estimating quantile treatment effect on the original scale of the outcome variable: a case study of common cold treatments.
Zinc Common Cold Meta-AnalysisQuantile treatment effect (QTE) analysis is more informative as it estimates the effect of treatment across the whole population.4Hemilä H (2025)Estimating quantile treatment effect on the original scale of the outcome variable: a case study of common cold treatments.

Source documents

  1. Integrating Meta-QTL mapping and RNA-seq analysis identifies candidate genes for cold tolerance at rice seedling stage
  2. Estimating quantile treatment effect on the original scale of the outcome variable: a case study of common cold treatments.