ArticleScientific data2018
Computational workflow to study the seasonal variation of secondary metabolites in nine different bryophytes.
Article in Scientific data, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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Who cites it
9 citing papers in PubMed.
- Impact of in vitro phytohormone treatments on the metabolome of the leafy liverwort Radula complanata (L.) Dumort.Metabolomics : Official journal of the Metabolomic Society · 2023Article
- Untargeted Metabolomics for Integrative Taxonomy: Metabolomics, DNA Marker-Based Sequencing, and Phenotype Bioimaging.Plants (Basel, Switzerland) · 2023Article
- Untargeted In Silico Compound Classification-A Novel Metabolomics Method to Assess the Chemodiversity in Bryophytes.International journal of molecular sciences · 2021Article
- Bibenzyls and bisbybenzyls of bryophytic origin as promising source of novel therapeutics: pharmacology, synthesis and structure-activity.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2020Review
- Chemical Diversity and Classification of Secondary Metabolites in Nine Bryophyte Species.Metabolites · 2019Article
- PhenoMeNal: processing and analysis of metabolomics data in the cloud.GigaScience · 2019Article
- Seasonal variation of secondary metabolites in nine different bryophytes.Ecology and evolution · 2018Article
- Computational workflow to study the seasonal variation of secondary metabolites in nine different bryophytes.Scientific data · 2018Article
- Current Challenges in Plant Eco-Metabolomics.International journal of molecular sciences · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In Eco-Metabolomics interactions are studied of non-model organisms in their natural environment and relations are made between biochemistry and ecological function. Current challenges when processing such metabolomics data involve complex experiment designs which are often carried out in large field campaigns involving multiple study factors, peak detection parameter settings, the high variation of metabolite profiles and the analysis of non-model species with scarcely characterised metabolomes. Here, we present a dataset generated from 108 samples of nine bryophyte species obtained in four seasons using an untargeted liquid chromatography coupled with mass spectrometry acquisition method (LC/MS). Using this dataset we address the current challenges when processing Eco-Metabolomics data. Here, we also present a reproducible and reusable computational workflow implemented in Galaxy focusing on standard formats, data import, technical validation, feature detection, diversity analysis and multivariate statistics. We expect that the representative dataset and the reusable processing pipeline will facilitate future studies in the research field of Eco-Metabolomics.
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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.