Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Plant stress biomarkers from biosimulations: the Transcriptome-To-Metabolome (TTM) technology - effects of drought stress on rice.

Plant biology (Stuttgart, Germany) - 1 Jan 2015

Phelix C F, Feltus F A

Abstract excerpt

Measuring biomarkers from plant tissue samples is challenging and expensive when the desire is to integrate transcriptomics, fluxomics, metabolomics, lipidomics, proteomics, physiomics and phenomics. We present a computational biology method where only the transcriptome needs to be measured and is used to derive a set of parameters for deterministic kinetic models of metabolic pathways. The technology is called...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Droughts
Share to Gibberellins
Share to Metabolome

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Phosphatidylglycerols

Share to Secondary Metabolism

Share to Stress, Physiological

Share to Trehalose

Source

Identifiers

PMID: 24985701
DOI: 10.1111/plb.12221

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Plant stress biomarkers from biosimulations: the Transcriptome-To-Metabolome (TTM) technology - effects of drought stress on rice.PMID 24985701Read ↗

Identification of drought tolerance markers in a diverse population of rice cultivars by expression and metabolite profiling.Semantic proximity Read ↗

Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism.Semantic proximity Read ↗

Metabolome-wide association studies for agronomic traits of rice.Semantic proximity Read ↗

Exploring molecular backgrounds of quality traits in rice by predictive models based on high-coverage metabolomics.Semantic proximity Read ↗

Metabolomics--the link between genotypes and phenotypes.Semantic proximity Read ↗

Evaluating metabolic and genomic data for predicting grain traits under high night temperature stress in rice.Semantic proximity Read ↗

The Contribution of Metabolomics to Systems Biology: Current Applications Bridging Genotype and Phenotype in Plant Science.Semantic proximity Read ↗

Discovering plant metabolic biomarkers for phenotype prediction using an untargeted approach.Semantic proximity Read ↗

Magnaporthe oryzae Systemic Defense Trigger 1 (MoSDT1)-Mediated Metabolites Regulate Defense Response in RiceSemantic proximity Read ↗

Integration of metabolomic and proteomic phenotypes: analysis of data covariance dissects starch and RFO metabolism from low and high temperature compensation response in Arabidopsis thaliana.Semantic proximity Read ↗

Leveraging non-targeted metabolite profiling via statistical genomics.Semantic proximity Read ↗

Combined Use of Genome-Wide Association Data and Correlation Networks Unravels Key Regulators of Primary Metabolism in Arabidopsis thaliana.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.