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Michael Hucka

Researcher at California Institute of Technology

Publications -  126
Citations -  15161

Michael Hucka is an academic researcher from California Institute of Technology. The author has contributed to research in topics: SBML & Systems Biology Ontology. The author has an hindex of 42, co-authored 124 publications receiving 13785 citations. Previous affiliations of Michael Hucka include University of Michigan.

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The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models.

TL;DR: This work summarizes the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks, a software-independent language for describing models common to research in many areas of computational biology.
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A community-driven global reconstruction of human metabolism

Ines Thiele, +53 more
- 01 May 2013 - 
TL;DR: Recon 2, a community-driven, consensus 'metabolic reconstruction', is described, which is the most comprehensive representation of human metabolism that is applicable to computational modeling and has improved topological and functional features.
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The Systems Biology Graphical Notation

TL;DR: The Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists, believes that it will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge.
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BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems

TL;DR: TheBioModels Database (), part of the international initiative BioModels.net, provides access to published, peer-reviewed, quantitative models of biochemical and cellular systems.
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Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

TL;DR: This protocol provides an overview of all new features of the COBRA Toolbox and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios.