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Find video protocols related to scientific articles indexed in Pubmed.
HepatoNet1: a comprehensive metabolic reconstruction of the human hepatocyte for the analysis of liver physiology.
Mol. Syst. Biol.
PUBLISHED: 07-08-2010
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We present HepatoNet1, the first reconstruction of a comprehensive metabolic network of the human hepatocyte that is shown to accomplish a large canon of known metabolic liver functions. The network comprises 777 metabolites in six intracellular and two extracellular compartments and 2539 reactions, including 1466 transport reactions. It is based on the manual evaluation of >1500 original scientific research publications to warrant a high-quality evidence-based model. The final network is the result of an iterative process of data compilation and rigorous computational testing of network functionality by means of constraint-based modeling techniques. Taking the hepatic detoxification of ammonia as an example, we show how the availability of nutrients and oxygen may modulate the interplay of various metabolic pathways to allow an efficient response of the liver to perturbations of the homeostasis of blood compounds.
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Modeling signal transduction in enzyme cascades with the concept of elementary flux modes.
J. Comput. Biol.
PUBLISHED: 06-16-2009
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Concepts such as elementary flux modes (EFMs) and extreme pathways are useful tools in the detection of non-decomposable routes (metabolic pathways) in biochemical networks. These methods are based on the fact that metabolic networks obey a mass balance condition. In signal transduction networks, that condition is of minor importance because it is the flow of information that matters. Nevertheless, it would be interesting to apply pathway detection methods to signaling systems. Here, we present a formalism by which this can be achieved in the case of enzyme cascades operating, for example, by phosphorylation and dephosphorylation. It is based on the ideas that the signal is not diminished along each route and that the system has to return to its original state after each signaling event. We illustrate the method by several simple prototypic single-phosphorylation and double-phosphorylation cascades, including convergent and divergent branching. Moreover, it is applied to a specific example from insulin signaling. (See online Supplementary Material at www.liebertonline.com.).
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On the evolutionary significance of the size and planarity of the proline ring.
Naturwissenschaften
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Proline is a proteinogenic amino acid in which the side chain forms a ring, the pyrrolidine ring. This is a five-membered ring made up of four carbons and one nitrogen. Here, we study the evolutionary significance of this ring size. It is shown that the size of the pyrrolidine ring has the advantage of being nearly planar and strain-free, based on a general mathematical assertion saying that the angular sum of a polygon is maximum if it is planar and convex. We also provide a sketch of the proof to this assertion. The optimality of the ring size of proline can be derived from a triangle inequality for angles. Quasi-planarity is physiologically significant because it allows an easier and evolutionarily old type of fit into binding grooves of proteins with which proline-rich proteins interact. Finally, we present a comparison with other planar, nearly planar and non-planar biomolecules such as neurotransmitters, hormones and toxins, involving, for example, aromatic rings, cyclopentanone and 1,3-dioxole.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.