ArticleJournal of the American Society for Mass Spectrometry2019
BLANKA: an Algorithm for Blank Subtraction in Mass Spectrometry of Complex Biological Samples.
Article in Journal of the American Society for Mass Spectrometry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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.
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
11 citing papers in PubMed.
- ReShuffle-MS: Region-Guided Data Augmentation Improves Artificial Intelligence-Based Resistance Prediction inMicroorganisms · 2026Article
- MALDI-TIMS-MSAnalytical chemistry · 2025Article
- Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data.Nature protocols · 2025Article
- Metabolomics of bacterial-fungal pairwise interactions reveal conserved molecular mechanisms.The Analyst · 2023Article
- Metabolomics of bacterial-fungal pairwise interactions reveal conserved molecular mechanisms.bioRxiv : the preprint server for biology · 2023Article
- "Omic" Approaches to Bacteria and Antibiotic Resistance Identification.International journal of molecular sciences · 2022Review
- Determination of Abundant Metabolite Matrix Adducts Illuminates the Dark Metabolome of MALDI-Mass Spectrometry Imaging Datasets.Analytical chemistry · 2021Article
- Creation and filtering of a recurrent spectral library of CHO cell metabolites and media components.Biotechnology and bioengineering · 2021Article
- Bacterial-fungal interactions revealed by genome-wide analysis of bacterial mutant fitness.Nature microbiology · 2021Article
- Food Phenotyping: Recording and Processing of Non-Targeted Liquid Chromatography Mass Spectrometry Data for Verifying Food Authenticity.Molecules (Basel, Switzerland) · 2020Review
- Reproducible molecular networking of untargeted mass spectrometry data using GNPS.Nature protocols · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Multispecies microbiome systems are known to be closely linked to human, animal, and plant life processes. The growing field of metabolomics presents the opportunity to detect changes in overall metabolomic profiles of microbial species interactions. These metabolomic changes provide insight into function of metabolites as they correlate to different species presence and the observed phenotypic changes, but detection of subtle changes is often difficult in samples with complex backgrounds. Natural environments such as soil and food contain many molecules that convolute mass spectrometry-based analyses, and identification of microbial metabolites amongst environmental metabolites is an informatics problem we begin to address here. Our microbes are grown on solid or liquid cheese curd media. This medium, which is necessary for microbial growth, contains high amounts of salts, lipids, and casein breakdown products which make statistical analyses using LC-MS/MS data difficult due to the high background from the media. We have developed a simple algorithm to carry out background subtraction from microbes grown on solid or liquid cheese curd media to aid in our ability to conduct statistical analyses so that we may prioritize metabolites for further structure elucidation. Graphical Abstract .
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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.