R
Rainer Breitling
Researcher at University of Manchester
Publications - 239
Citations - 21369
Rainer Breitling is an academic researcher from University of Manchester. The author has contributed to research in topics: Synthetic biology & Metabolomics. The author has an hindex of 65, co-authored 233 publications receiving 19231 citations. Previous affiliations of Rainer Breitling include University of Glasgow & University of Groningen.
Papers
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Microarray challenges in ecology
TL;DR: It is shown that experimental design and environmental confounders greatly influence the identification of candidate genes in ecological microarray studies, and that following several simple recommendations could facilitate the analysis of microarray data in ecological settings.
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A structured approach for the engineering of biochemical network models, illustrated for signalling pathways
TL;DR: A general approach is introduced that provides the foundations for a structured formal engineering of large-scale models of biochemical networks, using signal transduction as the main example.
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Expression of muscarinic receptor types in the primate ovary and evidence for nonneuronal acetylcholine synthesis.
Stephanie Fritz,Ignaz Wessler,Rainer Breitling,W. Rossmanith,Sergio R. Ojeda,Gregory A. Dissen,Abraham Amsterdam,Artur Mayerhofer +7 more
TL;DR: The ovary contains multiple MR, and GC of antral follicles are able to synthesize ACh, the ligand of MR, which is proposed to serve as an as yet unrecognized factor involved in the complex regulation of ovarian function in the primate.
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Machine Learning of Designed Translational Control Allows Predictive Pathway Optimization in Escherichia coli
Adrian J. Jervis,Pablo Carbonell,Maria Vinaixa,Mark S. Dunstan,Katherine A. Hollywood,Christopher J. Robinson,Nicholas J. W. Rattray,Cunyu Yan,Neil Swainston,Andrew Currin,Rehana Sung,Helen S. Toogood,Sandra Taylor,Jean-Loup Faulon,Jean-Loup Faulon,Rainer Breitling,Eriko Takano,Nigel S. Scrutton +17 more
TL;DR: The implementation of machine learning algorithms to model the RBS sequence-phenotype relationship from representative subsets of large combinatorial RBS libraries allowing the accurate prediction of optimal high-producers is presented.
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Steps towards the synthetic biology of polyketide biosynthesis
TL;DR: The lessons learned from the classical engineering of polyketide synthases are discussed and indicate their importance when attempting to engineer biosynthetic pathways using synthetic biology approaches for the introduction of novelty and overexpression of products in a controllable manner.