Jacky L. Snoep mainly focuses on Biochemistry, Yeast, Glycolysis, Reuse and Saccharomyces cerevisiae. Biochemistry connects with themes related to Lactococcus lactis in his study. Microfluidic chamber and Sustained oscillations is closely connected to Cell biology in his research, which is encompassed under the umbrella topic of Yeast.
His Glycolysis study integrates concerns from other disciplines, such as Flux and Adenosine triphosphate. His Reuse research is multidisciplinary, incorporating elements of Programming language, Set, User interface and Encoding. His biological study spans a wide range of topics, including Software, Modeling language, Executable and Computational science.
Jacky L. Snoep mainly investigates Biochemistry, Systems biology, Glycolysis, Yeast and Cell biology. Jacky L. Snoep performs multidisciplinary study in Biochemistry and Plasmodium falciparum in his work. His biological study deals with issues like Data science, which deal with fields such as Data integration, Component and Data management.
His work on Phosphofructokinase as part of general Glycolysis research is frequently linked to Limit cycle oscillation, thereby connecting diverse disciplines of science. His research integrates issues of Biological system and Single-cell analysis in his study of Yeast. His work on Signal transduction is typically connected to DNA supercoil as part of general Cell biology study, connecting several disciplines of science.
Jacky L. Snoep mostly deals with Biochemistry, Systems biology, Data science, Plasmodium falciparum and Yeast. His study in Systems biology is interdisciplinary in nature, drawing from both Management science and Systems engineering. His Data science research incorporates elements of Data integration, Reuse, Component and Data management.
His Reuse study incorporates themes from Table and Bioinformatics. In his study, Drug target is strongly linked to Biological system, which falls under the umbrella field of Yeast. Within one scientific family, Jacky L. Snoep focuses on topics pertaining to Adenosine triphosphate under Flux, and may sometimes address concerns connected to Phosphofructokinase and Glycolysis.
His primary areas of study are Biochemistry, Systems biology, Data science, Plasmodium falciparum and Context. The Biochemistry study combines topics in areas such as Organism and Pathogen. The various areas that Jacky L. Snoep examines in his Systems biology study include Domain and Data management.
The concepts of his Data science study are interwoven with issues in Data integration, Reuse and Component. His research in Reuse intersects with topics in Identifier, The Internet and Relevance. His Component research includes elements of Table, Interoperability and Bioinformatics.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
The Systems Biology Graphical Notation
Nicolas Le Novere;Michael Hucka;Huaiyu Mi;Stuart Moodie.
Nature Biotechnology (2009)
BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems
Nicolas Le Novère;Benjamin J. Bornstein;Alexander Broicher;Mélanie Courtot.
Nucleic Acids Research (2006)
Can yeast glycolysis be understood in terms of in vitro kinetics of the constituent enzymes? Testing biochemistry.
Bas Teusink;Jutta Passarge;Corinne A. Reijenga;Eugenia Esgalhado.
FEBS Journal (2000)
Minimum information requested in the annotation of biochemical models (MIRIAM)
Nicolas Le Novère;Andrew Finney;Michael Hucka;Upinder S. Bhalla.
Nature Biotechnology (2005)
Biomodels database: an enhanced curated and annotated resource for published quantitative kinetic models
Chen Li;Marco Donizelli;Nicolas Rodriguez;Harish Dharuri.
BMC Systems Biology (2010)
The Steady-State Internal Redox State (NADH/NAD) Reflects the External Redox State and Is Correlated with Catabolic Adaptation in Escherichia coli
M.R. de Graef;S.V. Alexeeva;J.L. Snoep;M.J. Teixeira De Mattos.
Journal of Bacteriology (1999)
The glycolytic flux in Escherichia coli is controlled by the demand for ATP.
Brian J. Koebmann;Hans V. Westerhoff;Jacky L. Snoep;Dan Nilsson.
Journal of Bacteriology (2002)
Web-based kinetic modelling using JWS Online
Brett G. Olivier;Jacky L. Snoep.
Metabolic engineering of lactic acid bacteria, the combined approach: kinetic modelling, metabolic control and experimental analysis
Marcel H. N. Hoefnagel;Marjo J. C. Starrenburg;Dirk E. Martens;Jeroen Hugenholtz.
Reproducible computational biology experiments with SED-ML--the Simulation Experiment Description Markup Language.
Dagmar Waltemath;Richard R. Adams;Frank T. Bergmann;Michael Hucka.
BMC Systems Biology (2011)
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