Accurate prediction of in vivo protein abundances by coupling constraint-based modelling and machine learning

Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0

(2022) Iván Domenzain et al.   Nature Communications

Proteome Regulation Patterns Determine Escherichia coli Wild-Type and Mutant Phenotypes

(2021) Tobias B. Alter et al.   mSystems

Maximization of non-idle enzymes improves the coverage of the estimated maximal in vivo enzyme catalytic rates in Escherichia coli

(2021) Rudan Xu et al.   BIOINFORMATICS

Protein Abundance Prediction Through Machine Learning Methods

(2021) Mauricio Ferreira et al.   JOURNAL OF MOLECULAR BIOLOGY

Automatic construction of metabolic models with enzyme constraints

(2020) Pavlos Stephanos Bekiaris et al.   BMC BIOINFORMATICS

Mass-spectrometry-based draft of the Arabidopsis proteome

(2020) Julia Mergner et al.   NATURE

Absolute yeast mitochondrial proteome quantification reveals trade-off between biosynthesis and energy generation during diauxic shift

(2020) Francesca Di Bartolomeo et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Improving the prediction accuracy of protein abundance in Escherichia coli using mRNA accessibility

(2020) Goro Terai et al.   NUCLEIC ACIDS RESEARCH

Kinetic profiling of metabolic specialists demonstrates stability and consistency of in vivo enzyme turnover numbers

(2020) David Heckmann et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

BRENDA, the ELIXIR core data resource in 2021: new developments and updates

(2020) Antje Chang et al.   NUCLEIC ACIDS RESEARCH

The Gene Ontology resource: enriching a GOld mine

(2020) et al.   NUCLEIC ACIDS RESEARCH

A Review on Quantitative Multiplexed Proteomics

(2019) Nishant Pappireddi et al.   CHEMBIOCHEM

Yeast Systems Biology: Model organism and Cell Factory

(2019) Jens Nielsen   Biotechnology Journal

Quantification and discovery of sequence determinants of protein‐per‐mRNA amount in 29 human tissues

(2019) Basak Eraslan et al.   Molecular Systems Biology

Elucidation of Codon Usage Signatures across the Domains of Life

(2019) Eva Maria Novoa et al.   MOLECULAR BIOLOGY AND EVOLUTION

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

(2019) Trang T Le et al.   BIOINFORMATICS

A consensus S. cerevisiae metabolic model Yeast8 and its ecosystem for comprehensively probing cellular metabolism

(2019) Hongzhong Lu et al.   Nature Communications

Joint learning improves protein abundance prediction in cancers

(2019) Hongyang Li et al.   BMC BIOLOGY

Adaptation to the coupling of glycolysis to toxic methylglyoxal production in tpiA deletion strains of Escherichia coli requires synchronized and counterintuitive genetic changes

(2018) Douglas McCloskey et al.   METABOLIC ENGINEERING

Adaptive laboratory evolution resolves energy depletion to maintain high aromatic metabolite phenotypes in Escherichia coli strains lacking the Phosphotransferase System

(2018) Douglas McCloskey et al.   METABOLIC ENGINEERING

Multiple Optimal Phenotypes Overcome Redox and Glycolytic Intermediate Metabolite Imbalances in Escherichia coli pgi Knockout Evolutions

(2018) Douglas McCloskey et al.   APPLIED AND ENVIRONMENTAL MICROBIOLOGY

Growth Adaptation of gnd and sdhCB Escherichia coli Deletion Strains Diverges From a Similar Initial Perturbation of the Transcriptome

(2018) Douglas McCloskey et al.   Frontiers in Microbiology

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

(2018) David Heckmann et al.   Nature Communications

Standardization approaches in absolute quantitative proteomics with mass spectrometry

(2017) Francisco Calderón-Celis et al.   MASS SPECTROMETRY REVIEWS

Improving the phenotype predictions of a yeast genome‐scale metabolic model by incorporating enzymatic constraints

(2017) Benjamín J Sánchez et al.   Molecular Systems Biology

Quantitative proteomics: challenges and opportunities in basic and applied research

(2017) Olga T Schubert et al.   Nature Protocols

Absolute Quantification of Protein and mRNA Abundances Demonstrate Variability in Gene-Specific Translation Efficiency in Yeast

(2017) Petri-Jaan Lahtvee et al.   Cell Systems

Global characterization of in vivo enzyme catalytic rates and their correspondence to in vitrokcatmeasurements

(2016) Dan Davidi et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Quantitative prediction of genome-wide resource allocation in bacteria

(2015) Anne Goelzer et al.   METABOLIC ENGINEERING

Proteome reallocation in Escherichia coli with increasing specific growth rate

(2015) Karl Peebo et al.   Molecular BioSystems

The quantitative and condition-dependent Escherichia coli proteome

(2015) Alexander Schmidt et al.   NATURE BIOTECHNOLOGY

Predicting the Dynamics of Protein Abundance

(2014) Ahmed M. Mehdi et al.   MOLECULAR & CELLULAR PROTEOMICS

Escherichia coli achieves faster growth by increasing catalytic and translation rates of proteins

(2013) Kaspar Valgepea et al.   Molecular BioSystems

Quantitative proteomics in the field of microbiology

(2013) Andreas Otto et al.   PROTEOMICS

clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters

(2012) Guangchuang Yu et al.   OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY

Prediction of Microbial Growth Rate versus Biomass Yield by a Metabolic Network with Kinetic Parameters

(2012) Roi Adadi et al.   PLoS Computational Biology

Integrative analysis of transcriptomic and proteomic data of Desulfovibrio vulgaris: a non-linear model to predict abundance of undetected proteins

(2009) Wandaliz Torres-García et al.   BIOINFORMATICS