ArticleBioinformatics (Oxford, England)2013
MeltDB 2.0-advances of the metabolomics software system.
Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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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.
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.
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Who cites it
27 citing papers in PubMed, 102 citations in OpenAlex.
- Metabolomics and Artificial Intelligence (AI) assisted metabolomics in the diagnosis of non-tuberculous mycobacterial infections: progress and challenges.New microbes and new infections · 2026Review
- Analyzing Plant Low-Molecular-Weight Polar Metabolites: A GC-MS Approach.Plants (Basel, Switzerland) · 2026Review
- CE-MS-Based Clinical Metabolomics of Human Plasma.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Specific activation of the integrated stress response uncovers regulation of central carbon metabolism and lipid droplet biogenesis.Nature communications · 2024Article
- Techniques, Databases and Software Used for Studying Polar Metabolites and Lipids of Gastrointestinal Parasites.Animals : an open access journal from MDPI · 2024Review
- Survey for Computer-Aided Tools and Databases in Metabolomics.Metabolites · 2022Review
- MetHoS: a platform for large-scale processing, storage and analysis of metabolomics data.BMC bioinformatics · 2022Article
- Plants Metabolome Study: Emerging Tools and Techniques.Plants (Basel, Switzerland) · 2021Review
- Discrepancies in metabolomic biomarker identification from patient-derived lung cancer revealed by combined variation in data pre-treatment and imputation methods.Metabolomics : Official journal of the Metabolomic Society · 2021Article
- Ranking Metabolite Sets by Their Activity Levels.Metabolites · 2021Article
- Food Phenotyping: Recording and Processing of Non-Targeted Liquid Chromatography Mass Spectrometry Data for Verifying Food Authenticity.Molecules (Basel, Switzerland) · 2020Review
- Metabolomics: A Way Forward for Crop Improvement.Metabolites · 2019Review
- Analytical Methods for Detection of Plant Metabolomes Changes in Response to Biotic and Abiotic Stresses.International journal of molecular sciences · 2019Review
- FELLA: an R package to enrich metabolomics data.BMC bioinformatics · 2018Article
- Missing value imputation for LC-MS metabolomics data by incorporating metabolic network and adduct ion relations.Bioinformatics (Oxford, England) · 2018Article
- Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data.Scientific reports · 2018Article
- GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies.PLoS computational biology · 2018Article
- compMS2Miner: An Automatable Metabolite Identification, Visualization, and Data-Sharing R Package for High-Resolution LC-MS Data Sets.Analytical chemistry · 2017Article
- Network Marker Selection for Untargeted LC-MS Metabolomics Data.Journal of proteome research · 2017Article
- Mixture model normalization for non-targeted gas chromatography/mass spectrometry metabolomics data.BMC bioinformatics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationThe research area metabolomics achieved tremendous popularity and development in the last couple of years. Owing to its unique interdisciplinarity, it requires to combine knowledge from various scientific disciplines. Advances in the high-throughput technology and the consequently growing quality and quantity of data put new demands on applied analytical and computational methods. Exploration of finally generated and analyzed datasets furthermore relies on powerful tools for data mining and visualization.
resultsTo cover and keep up with these requirements, we have created MeltDB 2.0, a next-generation web application addressing storage, sharing, standardization, integration and analysis of metabolomics experiments. New features improve both efficiency and effectivity of the entire processing pipeline of chromatographic raw data from pre-processing to the derivation of new biological knowledge. First, the generation of high-quality metabolic datasets has been vastly simplified. Second, the new statistics tool box allows to investigate these datasets according to a wide spectrum of scientific and explorative questions. AVAILABILITY: The system is publicly available at https://meltdb.cebitec.uni-bielefeld.de. A login is required but freely available.
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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.