Machine Learning Applications for Mass Spectrometry-Based Metabolomics

Migrating from partial least squares discriminant analysis to artificial neural networks: a comparison of functionally equivalent visualisation and feature contribution tools using jupyter notebooks

(2020) Kevin M. Mendez et al.   Metabolomics

Software tools, databases and resources in metabolomics: updates from 2018 to 2019

(2020) Keiron O’Shea et al.   Metabolomics

MESSAR: Automated recommendation of metabolite substructures from tandem mass spectra

(2020) Youzhong Liu et al.   PLoS One

Discrimination of rosé wines using shotgun metabolomics with a genetic algorithm and MS ion intensity ratios

(2020) Mélodie Gil et al.   Scientific Reports

MOTA: Network-Based Multi-Omic Data Integration for Biomarker Discovery

(2020) Ziling Fan et al.   Metabolites

DeepSpectra: An end-to-end deep learning approach for quantitative spectral analysis

(2019) Xiaolei Zhang et al.   ANALYTICA CHIMICA ACTA

DIABLO: an integrative approach for identifying key molecular drivers from multi-omic assays

(2019) Amrit Singh et al.   BIOINFORMATICS

A hybrid and exploratory approach to knowledge discovery in metabolomic data

(2019) Dhouha Grissa et al.   DISCRETE APPLIED MATHEMATICS

Simulation and reconstruction of metabolite-metabolite association networks using a metabolic dynamic model and correlation based-algorithms

(2019) sanjeevan jahagirdar@ et al.   JOURNAL OF PROTEOME RESEARCH

Rapid Prediction of Electron–Ionization Mass Spectrometry Using Neural Networks

(2019) Jennifer N. Wei et al.   ACS Central Science

Linking genetic, metabolic and phenotypic diversity among S. cerevisiae strains using multi-omics associations

(2019) Kang Kang et al.   GigaScience

SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information

(2019) Kai Dührkop et al.   NATURE METHODS

Revelation of the metabolic pathway of hederacoside C using an innovative data analysis strategy for dynamic multiclass biotransformation experiments

(2019) Laura Peeters et al.   JOURNAL OF CHROMATOGRAPHY A

Comprehensive and Empirical Evaluation of Machine Learning Algorithms for Small Molecule LC Retention Time Prediction

(2019) Robbin Bouwmeester et al.   ANALYTICAL CHEMISTRY

Systematic Error Removal Using Random Forest for Normalizing Large-Scale Untargeted Lipidomics Data

(2019) Sili Fan et al.   ANALYTICAL CHEMISTRY

Integrating a generalized data analysis workflow with the Single-probe mass spectrometry experiment for single cell metabolomics

(2019) Renmeng Liu et al.   ANALYTICA CHIMICA ACTA

Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics

(2019) Zhichao Liu et al.   ANALYTICAL CHEMISTRY

Deep MS/MS-Aided Structural-Similarity Scoring for Unknown Metabolite Identification

(2019) Hongchao Ji et al.   ANALYTICAL CHEMISTRY

Using deep learning to evaluate peaks in chromatographic data

(2019) Anne Bech Risum et al.   TALANTA

Lessons from Two Design–Build–Test–Learn Cycles of Dodecanol Production in Escherichia coli Aided by Machine Learning

(2019) Paul Opgenorth et al.   ACS Synthetic Biology

Deep learning for vibrational spectral analysis: Recent progress and a practical guide

(2019) Jie Yang et al.   ANALYTICA CHIMICA ACTA

Scaling tree-based automated machine learning to biomedical big data with a feature set selector

(2019) Trang T Le et al.   BIOINFORMATICS

Machine and deep learning meet genome-scale metabolic modeling

(2019) Guido Zampieri et al.   PLoS Computational Biology

Computational Methods for the Discovery of Metabolic Markers of Complex Traits

(2019) Michael Lee et al.   Metabolites

Improved Small Molecule Identification through Learning Combinations of Kernel Regression Models

(2019) Céline Brouard et al.   Metabolites

Deep Neural Networks for Classification of LC-MS Spectral Peaks

(2019) Edward D. Kantz et al.   ANALYTICAL CHEMISTRY

pseudoQC: A Regression‐Based Simulation Software for Correction and Normalization of Complex Metabolomics and Proteomics Datasets

(2019) Shisheng Wang et al.   PROTEOMICS

Uncertainty reduction in biochemical kinetic models: Enforcing desired model properties

(2019) Ljubisa Miskovic et al.   PLoS Computational Biology

Multi-Omics Analysis of Fatty Alcohol Production in Engineered Yeasts Saccharomyces cerevisiae and Yarrowia lipolytica

(2019) Jonathan Dahlin et al.   Frontiers in Genetics

Normalizing Untargeted Periconceptional Urinary Metabolomics Data: A Comparison of Approaches

(2019) Ana K. Rosen Vollmar et al.   Metabolites

WiPP: Workflow for Improved Peak Picking for Gas Chromatography-Mass Spectrometry (GC-MS) Data

(2019) Borgsmüller et al.   Metabolites

Random forest-based imputation outperforms other methods for imputing LC-MS metabolomics data: a comparative study

(2019) Marietta Kokla et al.   BMC BIOINFORMATICS

The application of artificial neural networks in metabolomics: a historical perspective

(2019) Kevin M. Mendez et al.   Metabolomics

A comparative evaluation of the generalised predictive ability of eight machine learning algorithms across ten clinical metabolomics data sets for binary classification

(2019) Kevin M. Mendez et al.   Metabolomics

Learning representations of microbe–metabolite interactions

(2019) James T. Morton et al.   NATURE METHODS

Bayesian inference of metabolic kinetics from genome-scale multiomics data

(2019) Peter C. St. John et al.   PLoS Computational Biology

Deep Learning for the Precise Peak Detection in High-Resolution LC–MS Data

(2019) Arsenty D. Melnikov et al.   ANALYTICAL CHEMISTRY

BayesMetab: treatment of missing values in metabolomic studies using a Bayesian modeling approach

(2019) Jasmit Shah et al.   BMC BIOINFORMATICS

Non-invasive diagnosis of non-alcoholic steatohepatitis and fibrosis with the use of omics and supervised learning: A proof of concept study

(2019) Nikolaos Perakakis et al.   METABOLISM-CLINICAL AND EXPERIMENTAL

Machine learning distilled metabolite biomarkers for early stage renal injury

(2019) Yan Guo et al.   Metabolomics

Multiple Compounds Recognition from The Tandem Mass Spectral Data Using Convolutional Neural Network

(2019) Jiali Lv et al.   MOLECULES

The METLIN small molecule dataset for machine learning-based retention time prediction

(2019) Xavier Domingo-Almenara et al.   Nature Communications

From Samples to Insights into Metabolism: Uncovering Biologically Relevant Information in LC-HRMS Metabolomics Data

(2019) Julijana Ivanisevic et al.   Metabolites

High-throughput screening for improved microbial cell factories, perspective and promise

(2019) Michael D Leavell et al.   CURRENT OPINION IN BIOTECHNOLOGY

Recent advances on constraint-based models by integrating machine learning

(2019) Pratip Rana et al.   CURRENT OPINION IN BIOTECHNOLOGY

OUP accepted manuscript

(2018)   BRIEFINGS IN BIOINFORMATICS

MiYA, an efficient machine-learning workflow in conjunction with the YeastFab assembly strategy for combinatorial optimization of heterologous metabolic pathways in Saccharomyces cerevisiae

(2018) Yikang Zhou et al.   METABOLIC ENGINEERING

KniMet: a pipeline for the processing of chromatography–mass spectrometry metabolomics data

(2018) Sonia Liggi et al.   Metabolomics

Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets

(2018) Ricard Argelaguet et al.   Molecular Systems Biology

Uncertainty estimation and misclassification probability for classification models based on discriminant analysis and support vector machines

(2018) Camilo L.M. Morais et al.   ANALYTICA CHIMICA ACTA

Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data

(2018) Runmin Wei et al.   Scientific Reports

A Multi-omic Association Study of Trimethylamine N-Oxide

(2018) Ohad Manor et al.   Cell Reports

Machine Learning Predicts the Yeast Metabolome from the Quantitative Proteome of Kinase Knockouts

(2018) Aleksej Zelezniak et al.   Cell Systems

Sample-Size Planning for Multivariate Data: A Raman-Spectroscopy-Based Example

(2018) Nairveen Ali et al.   ANALYTICAL CHEMISTRY

Tools and resources for metabolomics research community: A 2017-2018 update

(2018) Biswapriya B. Misra et al.   ELECTROPHORESIS

PubChem 2019 update: improved access to chemical data

(2018) Sunghwan Kim et al.   NUCLEIC ACIDS RESEARCH

Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models

(2018) David Heckmann et al.   Nature Communications

Machine Learning of Designed Translational Control Allows Predictive Pathway Optimization in Escherichia coli

(2018) Adrian J. Jervis et al.   ACS Synthetic Biology

Genome-scale mutational signatures of aflatoxin in cells, mice, and human tumors

(2017) Mi Ni Huang et al.   GENOME RESEARCH

HMDB 4.0: the human metabolome database for 2018

(2017) David S Wishart et al.   NUCLEIC ACIDS RESEARCH

Global chemical analysis of biology by mass spectrometry

(2017) Alexander A. Aksenov et al.   Nature Reviews Chemistry

Integration of metabolomics, lipidomics and clinical data using a machine learning method

(2016) Animesh Acharjee et al.   BMC BIOINFORMATICS

Deep learning in bioinformatics

(2016) Seonwoo Min et al.   BRIEFINGS IN BIOINFORMATICS

iSCHRUNK – I n S ilico Approach to Ch aracterization and R eduction of Un certainty in the K inetic Models of Genome-scale Metabolic Networks

(2016) Stefano Andreozzi et al.   METABOLIC ENGINEERING

Non-targeted UHPLC-MS metabolomic data processing methods: a comparative investigation of normalisation, missing value imputation, transformation and scaling

(2016) Riccardo Di Guida et al.   Metabolomics

Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

(2016) Mingxun Wang et al.   NATURE BIOTECHNOLOGY

Revealing disease-associated pathways by network integration of untargeted metabolomics

(2016) Leila Pirhaji et al.   NATURE METHODS

Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli

(2016) Minseung Kim et al.   Nature Communications

Rapid Prediction of Bacterial Heterotrophic Fluxomics Using Machine Learning and Constraint Programming

(2016) Stephen Gang Wu et al.   PLoS Computational Biology

SUMOFLUX: A Generalized Method for Targeted 13C Metabolic Flux Ratio Analysis

(2016) Maria Kogadeeva et al.   PLoS Computational Biology

Integrative Analysis of Proteomic, Glycomic, and Metabolomic Data for Biomarker Discovery

(2016) Minkun Wang et al.   IEEE Journal of Biomedical and Health Informatics

Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

(2016) Elizabeth Brunk et al.   Cell Systems

Review, Evaluation, and Discussion of the Challenges of Missing Value Imputation for Mass Spectrometry-Based Label-Free Global Proteomics

(2015) Bobbie-Jo M. Webb-Robertson et al.   JOURNAL OF PROTEOME RESEARCH

UPLC–MS retention time prediction: a machine learning approach to metabolite identification in untargeted profiling

(2015) Arnaud M. Wolfer et al.   Metabolomics

Modern modelling techniques are data hungry: a simulation study for predicting dichotomous endpoints

(2015) Tjeerd van der Ploeg et al.   BMC Medical Research Methodology

isoMETLIN: A Database for Isotope-Based Metabolomics

(2014) Kevin Cho et al.   ANALYTICAL CHEMISTRY

Application of support vector machines to metabolomics experiments with limited replicates

(2014) Joshua Heinemann et al.   Metabolomics

Metabolite Profiling of a NIST Standard Reference Material for Human Plasma (SRM 1950): GC-MS, LC-MS, NMR, and Clinical Laboratory Analyses, Libraries, and Web-Based Resources

(2013) Yamil Simón-Manso et al.   ANALYTICAL CHEMISTRY

Reflections on univariate and multivariate analysis of metabolomics data

(2013) Edoardo Saccenti et al.   Metabolomics

PRIMe Update: Innovative Content for Plant Metabolomics and Integration of Gene Expression and Metabolite Accumulation

(2013) Tetsuya Sakurai et al.   PLANT AND CELL PHYSIOLOGY

Metabolite identification and molecular fingerprint prediction through machine learning

(2012) M. Heinonen et al.   BIOINFORMATICS

Data mining in the Life Sciences with Random Forest: a walk in the park or lost in the jungle?

(2012) W. G. Touw et al.   BRIEFINGS IN BIOINFORMATICS

Translational biomarker discovery in clinical metabolomics: an introductory tutorial

(2012) Jianguo Xia et al.   Metabolomics

An accelerated workflow for untargeted metabolomics using the METLIN database

(2012) Ralf Tautenhahn et al.   NATURE BIOTECHNOLOGY

RIKEN tandem mass spectral database (ReSpect) for phytochemicals: A plant-specific MS/MS-based data resource and database

(2012) Yuji Sawada et al.   PHYTOCHEMISTRY

Toward Global Metabolomics Analysis with Hydrophilic Interaction Liquid Chromatography–Mass Spectrometry: Improved Metabolite Identification by Retention Time Prediction

(2011) Darren J. Creek et al.   ANALYTICAL CHEMISTRY

Missing values in mass spectrometry based metabolomics: an undervalued step in the data processing pipeline

(2011) Olga Hrydziuszko et al.   Metabolomics

ChemSpider: An Online Chemical Information Resource

(2010) Harry E. Pence et al.   JOURNAL OF CHEMICAL EDUCATION

PaDEL-descriptor: An open source software to calculate molecular descriptors and fingerprints

(2010) Chun Wei Yap   JOURNAL OF COMPUTATIONAL CHEMISTRY

MassBank: a public repository for sharing mass spectral data for life sciences

(2010) Hisayuki Horai et al.   JOURNAL OF MASS SPECTROMETRY

How mathematical modelling elucidates signalling in Bacillus subtilis

(2010) Ulf W. Liebal et al.   MOLECULAR MICROBIOLOGY

Support Vector Machines for classification and regression

(2009) Richard G. Brereton et al.   ANALYST

Combining tissue transcriptomics and urine metabolomics for breast cancer biomarker identification

(2009) Hojung Nam et al.   BIOINFORMATICS