ArticleAnalytical chemistry2020
Chemical Class Prediction of Unknown Biomolecules Using Ion Mobility-Mass Spectrometry and Machine Learning: Supervised Inference of Feature Taxonomy from Ensemble Randomization.
Article in Analytical chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Peak2Patch: High-Fidelity Functional Group Identification through Attention-Based Fusion of Infrared and Mass Spectra.ACS omega · 2026Article
- Untargeted metabolomics and lipidomics to study autophagy induction in mouse embryonic fibroblasts.Analytical and bioanalytical chemistry · 2026Article
- AnnoMe: user-defined classification of HR-MS/MS spectra for natural product discovery.Bioinformatics advances · 2026Article
- The exhaled breath pattern as a potential method for biometrics identification.Scientific reports · 2025Article
- Rapid Annotation Strategy forJournal of the American Society for Mass Spectrometry · 2025Article
- Recent Developments in Machine Learning for Mass Spectrometry.ACS measurement science au · 2024Review
- Improved analysis of derivatized steroid hormone isomers using ion mobility-mass spectrometry (IM-MS).Analytical and bioanalytical chemistry · 2023Article
- Collision Cross Section Prediction Based on Machine Learning.Molecules (Basel, Switzerland) · 2023Review
- CCS Predictor 2.0: An Open-Source Jupyter Notebook Tool for Filtering Out False Positives in Metabolomics.Analytical chemistry · 2022Article
- Improving confidence in lipidomic annotations by incorporating empirical ion mobility regression analysis and chemical class prediction.Bioinformatics (Oxford, England) · 2022Article
- Insights and prospects for ion mobility-mass spectrometry in clinical chemistry.Expert review of proteomics · 2022Article
- Multidimensional Separations of Intact Phase II Steroid Metabolites Utilizing LC-Ion Mobility-HRMS.Analytical chemistry · 2021Article
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
This work presents a machine learning algorithm referred to as the supervised inference of feature taxonomy from ensemble randomization (SIFTER), which supports the identification of features derived from untargeted ion mobility-mass spectrometry (IM-MS) experiments. SIFTER utilizes random forest machine learning on three analytical measurements derived from IM-MS (collision cross section, CCS), mass-to-charge (
Indexed as
Identifiers
What 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.