about
Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighboursMetabolic network topology reveals transcriptional regulatory signatures of type 2 diabetes.Contribution of network connectivity in determining the relationship between gene expression and metabolite concentration changes.Metabolic dependencies drive species co-occurrence in diverse microbial communitiesThe self-inhibitory nature of metabolic networks and its alleviation through compartmentalization.Functional Metabolomics Describes the Yeast Biosynthetic Regulome.The metabolic background is a global player in Saccharomyces gene expression epistasis.Flux coupling and transcriptional regulation within the metabolic network of the photosynthetic bacterium Synechocystis sp. PCC6803.Nutritional preferences of human gut bacteria reveal their metabolic idiosyncrasies.Cost-effective generation of precise label-free quantitative proteomes in high-throughput by microLC and data-independent acquisition.Precise label-free quantitative proteomes in high-throughput by microLC and data-independent SWATH acquisitionMachine Learning Predicts the Yeast Metabolome from the Quantitative Proteome of Kinase Knockouts
P50
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P50
description
researcher ORCID ID = 0000-0002-3098-9441
@en
name
Aleksej Zelezniak
@ast
Aleksej Zelezniak
@en
Aleksej Zelezniak
@es
Aleksej Zelezniak
@nl
type
label
Aleksej Zelezniak
@ast
Aleksej Zelezniak
@en
Aleksej Zelezniak
@es
Aleksej Zelezniak
@nl
prefLabel
Aleksej Zelezniak
@ast
Aleksej Zelezniak
@en
Aleksej Zelezniak
@es
Aleksej Zelezniak
@nl
P108
P108
P31
P496
0000-0002-3098-9441