Manfred Beckmann

发表

On the Interpretation of High Throughput MS Based Metabolomics Fingerprints with Random Forest

John Draper, David P. Enot, Manfred Beckmann, 2006, CompLife.

Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour 'rules'

Wanchang Lin, John Draper, David P. Enot, 2009, BMC Bioinformatics.

Biomarkers of whole-grain intake: contribution of alkylresorcinols and mammalian lignans to the metabolome

Lee Fawcett, Kirsten Brandt, John Draper, 2010 .

Metabolic Engineering, metabolite profiling and machine learning to investigate the phloem-mobile signal in systemic acquired resistance in tobacco

Douglas B. Kell, Royston Goodacre, Janet Taylor, 2002 .

Temporal metabolic partitioning of the yeast and protist cellular networks: the cell is a global scale-invariant (fractal or self-similar) multioscillator

Sonia Cortassa, David Lloyd, Manfred Beckmann, 2018, Journal of biomedical optics.

GC-MS Peak Labeling Under ArMet

Nigel W. Hardy, Nigel Hardy, John Draper, 2007 .

FluoroMatch: A Comprehensive Software for Non-Targeted PFAS Analysis

Jeremy P. Koelmel, John A. Bowden, John Draper, 2021, ISEE Conference Abstracts.

High-throughput, nontargeted metabolite fingerprinting using nominal mass flow injection electrospray mass spectrometry

Emilie Duval, John Draper, Manfred Beckmann, 2008, Nature Protocols.

Explanatory signal interpretation and metabolite identification strategies for nominal mass FIE-MS metabolite fingerprints

John Draper, Manfred Beckmann, M. Beckmann, 2008, Nature Protocols.

Preprocessing, classification modeling and feature selection using flow injection electrospray mass spectrometry metabolite fingerprint data

Wanchang Lin, John Draper, Manfred Beckmann, 2008, Nature Protocols.

Representation, comparison, and interpretation of metabolome fingerprint data for total composition analysis and quality trait investigation in potato cultivars.

John Draper, Manfred Beckmann, M. Beckmann, 2007, Journal of agricultural and food chemistry.

Rice blast infection of Brachypodium distachyon as a model system to study dynamic host/pathogen interactions

John Draper, Manfred Beckmann, N. Talbot, 2008, Nature Protocols.

The Scale-Free Dynamics of Eukaryotic Cells

Marc R. Roussel, Brian O'Rourke, David Lloyd, 2008, PloS one.

Dietary metabotype modelling predicts individual responses to dietary interventions

Joram M. Posma, Jeremy K. Nicholson, Elaine Holmes, 2020, Nature Food.

A proposed framework for the description of plant metabolomics experiments and their results

Nigel W. Hardy, Kazuki Saito, Oliver Fiehn, 2004, Nature Biotechnology.

Objective assessment of dietary patterns by use of metabolic phenotyping: a randomised, controlled, crossover trial

Rachel Gibson, Jeremiah Stamler, Torben Hansen, 2017, The lancet. Diabetes & endocrinology.

Predicting interpretability of metabolome models based on behavior, putative identity, and biological relevance of explanatory signals

John Draper, Manfred Beckmann, M. Beckmann, 2006, Proceedings of the National Academy of Sciences.

Original Article

Wanchang Lin, John C. Mathers, Gaëlle Favé, 1995 .

Fourier Transform Ion Cyclotron Resonance mass spectrometry for plant metabolite profiling and metabolite identification.

Royston Goodacre, J William Allwood, J. W. Allwood, 2012, Methods in molecular biology.

Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops.

Nigel W. Hardy, Oliver Fiehn, Janet Taylor, 2005, Proceedings of the National Academy of Sciences of the United States of America.