Narrow Results

With the rapid growth of microarray data, it has become a hot topic to reveal complex behaviors and functions of life system by studying the relationships among genes. In the process of reverse network modeling, the relationships with less relevance are generally not considered by determining a threshold when the relationships among genes are mined. However, there are no effective methods to determine the threshold up to now. It is worthwhile to note that the phenotypes of genetic diseases are generally regarded as external representation of the functions of genes. Therefore, two types of phenotype networks are constructed from gene and disease views, respectively, and through comparing these two types of phenotype networks, the threshold of gene network corresponding to a certain disease can be determined when their similarity reaches to maximum. Because the gene network is determined based on the relationships among phenotypes and phenotypes are external representation of the functions of genes, it is considered that relationships in the gene network may show functional relationships among genes in biological system. In this work, the thresholds 0.47 and 0.48 of gene network are determined based on Parkinson disease phenotypes. Furthermore, the validity of these thresholds is verified by the specificity and susceptibility of phenotype networks. Also, through comparing the structural parameters of gene networks for normal and disease stage at different thresholds, significant difference between the two gene networks at threshold 0.47 or 0.48 is found. The significant difference of structural parameters further verifies the efficiency of this method.

We study a discrete-time model of host–parasitoid interactions, where the host is subject to a strong Allee effect and the parasitoid is aggregated. The system may have multiple coexisting steady states and there are two host population thresholds. The hosts become extinct if it is below the Allee threshold. The other threshold depends on the Allee threshold beyond which the host also becomes extinct due to overcompensated density dependence. When the initial host population size is between the two thresholds, we derive a critical parasitoid population size above which both populations become extinct. The critical size depends on the degree of aggregation of parasitoids. It is shown that both populations are more likely to become extinct if parasitoid aggregation is increased. Numerical simulations reveal that a strong Allee effect on the host can stabilize the host–parasitoid interactions on one hand but may drive both populations to extinction on the other hand. Further, aggregation of the parasitoid can promote population persistence when the host is subject to a strong Allee effect with a large Allee threshold. However, a more aggregated parasitoid population is more vulnerable to extinction if the growth rate of hosts is large.

We use some examples to show that Metabolic Control Theory (MTC) not only allows the determination of the controlling steps of a metabolic network with the so-called control coefficients, but also leads to better understanding of the functioning of metabolic networks. The examples are taken partly from our own work on mitochondrial myopathies, partly from the literature:

— the threshold effect observed in mitochondria diseases;

— the problem of the diagnosis of complex I, II or III defects by measuring the NADH-cytochrome-c-reductase or the succinate-cytochrome-c-reductase activities with illustration by some cases. The possibility of a sum of control coefficients greater than one is also considered.