ArticleMethods in molecular biology (Clifton, N.J.)2024
Efficient and Powerful Integration of Targeted Metabolomics and Transcriptomics for Analyzing the Metabolism Behind Desirable Traits in Plants.
Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Functional analysis of LIPID TRANSFER PROTEIN 6 (LTP6) in pennycress and Arabidopsis reveals divergent roles in oil storage and seed coat development.The Plant journal : for cell and molecular biology · 2026Article
- Propelling sustainable energy: Multi-omics analysis of pennycress FATTY ACID ELONGATION1 knockout for biofuel production.Plant physiology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Through current mass spectrometry methods and multiple RNA-Seq technologies, large metabolomics and transcriptomics datasets are readily obtainable, which provide a powerful and global perspective on metabolism. Indeed, one "omics" method is often not enough to draw strong conclusions about metabolism. Combining and interpreting multiple "omics" datasets remains a challenging task that requires careful statistical considerations and pre-planning. Here we describe a protocol for obtaining high-quality metabolomics and transcriptomics datasets in developing plant embryos followed by a robust approach to integration of the two. This protocol is readily adjustable and scalable to any other metabolically active organ or tissue.
Indexed as
Identifiers
39068357What 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.