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Description: Complex networks appear in biology on many different levels: (1) All biochemical reactions taking place in a single cell constitute its metabolic network, where nodes are individual metabolites, and edges are metabolic reactions converting them to each other. (2) Virtually every one of these reactions is catalyzed by an enzyme and the specificity of this catalytic function is ensured by the key and lock principle of its physical interaction with the substrate. Often the functional enzyme is formed by several mutually interacting proteins. Thus the structure of the metabolic network is shaped by the network of physical interactions of cell's proteins with their substrates and each other. (3) The abundance and the level of activity of each of the proteins in the physical interaction network in turn is controlled by the regulatory network of the cell. Such regulatory network includes all of the multiple mechanisms in which proteins in the cell control each other including transcriptional and translational regulation, regulation of mRNA editing and its transport out of the nucleus, specific targeting of individual proteins for degradation, modification of their activity e.g. by phosphorylation/dephosphorylation or allosteric regulation, etc. To get some idea about the complexity and interconnectedness of protein-protein regulations in baker's yeast Saccharomyces Cerevisiae in Fig. 1 we show a part of the regulatory network corresponding to positive or negative regulations that regulatory proteins exert on each other. (4) On yet higher level individual cells of a multicellular organism exchange signals with each other. This gives rise to several new networks such as e.g. nervous, hormonal, and immune systems of animals. The intercellular signaling network stages the development of a multicellular organism from the fertilized egg. (5) Finally, on the grandest scale, the interactions between individual species in ecosystems determine their food webs. An interesting property of many biological ...
Date: November 17, 2003


Description: Bio-molecular networks lack the top-down design. Instead, selective forces of biological evolution shape them from raw material provided by random events such as gene duplications and single gene mutations. As a result individual connections in these networks are characterized by a large degree of randomness. One may wonder which connectivity patterns are indeed random, while which arose due to the network growth, evolution, and/or its fundamental design principles and limitations? Here we introduce a general method allowing one to construct a random null-model version of a given network while preserving the desired set of its low-level topological features, such as, e.g., the number of neighbors of individual nodes, the average level of modularity, preferential connections between particular groups of nodes, etc. Such a null-model network can then be used to detect and quantify the non-random topological patterns present in large networks. In particular, we measured correlations between degrees of interacting nodes in protein interaction and regulatory networks in yeast. It was found that in both these networks, links between highly connected proteins are systematically suppressed. This effect decreases the likelihood of cross-talk between different functional modules of the cell, and increases the overall robustness of a network by localizing effects of deleterious perturbations. It also teaches us about the overall computational architecture of such networks and points at the origin of large differences in the number of neighbors of individual nodes.
Date: November 17, 2003


Description: Gold has been used for immunocytochemistry since 1971 when Faulk and Taylor discovered adsorption of antibodies to colloidal gold. It is an ideal label for electron microscopy (EM) due to its high atomic number, which scatters electrons efficiently, and the fact that preparative methods have been developed to make uniform particles in the appropriate size range of 5 to 30 nm. Use in light microscopy (LM) generally requires silver enhancement (autometallography; AMG) of these small gold particles. Significant advances in this field since that time have included a better understanding of the conditions for best antibody adsorption, more regular gold size production, adsorption of other useful molecules, like protein A, and advances in silver enhancement. Many studies have also been accomplished showing the usefulness of these techniques to cell biology and biomedical research. A further advance in this field was the development of Nanogold{trademark}, a 1.4 nm gold cluster. A significant difference from colloidal gold is that Nanogold is actually a coordination compound containing a gold core covalently linked to surface organic groups. These in turn may be covalently attached to antibodies. This approach to immunolabeling has several advantages compared to colloidal gold such as vastly better penetration into tissues, generally greater sensitivity, and higher density of labeling. Since Nanogold is covalently coupled to antibodies, it may also be directly coupled to almost any protein, peptide, carbohydrate, or molecule of interest, including molecules which do not adsorb to colloidal gold. This increases the range of probes possible, and expands the applications of gold labeling.
Date: April 17, 2003