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Cell death is required for development and tissue homeostasis of all multicellular organisms. Cell death regulation is highly dependent on cell types and the physiological, pharmacological and pathological stimuli and can take distinctive forms. One mechanism that is conserved from C. elegans to humans to ensure desired cell death and to avoid unwanted cell death is through transcriptional regulation of cell death genes. Transcription regulation may be conferred by specific transcription factors or at a global level by chromatin remodeling activities. [ABSTRACT FROM AUTHOR]

Specification and specialization of cell and tissue structure and function is the result of the informational content and transcriptional programming of the entire genome. Because of this, whole genome/whole organism expression profiling has the potential to reveal tremendous amounts of information about the genome, specific cell types and tissues, and the evolution biological systems. Systems evolution can be studied by identifying and correlating conserved and diverged gene expression patterns of homologous and non-homologous cells and tissues, the functions of these implicated genes, and the corresponding genomic sequences and gene structural features that are conserved or diverged between multiple species' genomes. The combination of these approaches represents comparative transcriptomics or "orthologenomics", which has as its general hypothesis that improved understanding of any particular biological system can be derived through multispecies comparative analyses of genomes, transcriptionally active genes, and corresponding gene features. In this chapter we have sought to illustrate a test of this hypothesis using genes over-expressed in the central nervous system (CNS) tissues of humans and mice. The exercise lends strong support to the conjecture that these types of approaches will provide powerful new insights into specific systems that determine the health and disease of complex organisms. [ABSTRACT FROM AUTHOR]

Inspired by the immunity theory, a new immune-based dynamic intrusion response model, referred to as IDIR, is presented. An intrusion detection mechanism based on self-tolerance, clone selection, and immune surveillance, is established. The method, which uses antibody concentration to quantitatively describe the degree of intrusion danger, is demonstrated. And quantitative calculations of response cost and benefit are achieved. Then, the response decision-making mechanism of maximum response benefit is developed, and a dynamic intrusion response system which is self-adaptation is set up. The experiment results show that the proposed model is a good solution to intrusion response in the network. [ABSTRACT FROM AUTHOR]