LIFETIME AND TRANSIT TIME DISTRIBUTIONS |
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12.7Conclusions
In this chapter we suggested new types of experiments for large chemical and biochemical systems which lead to linear response even if the perturbations are large and the underlying kinetics is highly nonlinear. We have shown that the susceptibility functions in the response equations have a simple physical interpretation: they are given by the probability densities of the transit times and displacement vector of a given fragment crossing the system. We have developed methods for extracting connectivity, mechanistic, and kinetic information from response experiments.
Because of space limitations we considered only macroscopic kinetic systems, but the approach can be also applied to experiments of single-molecule kinetics [10]. The suggested approach is in an early stage of development. An important issue is extending the approach to nonneutral systems, for which the kinetic and transport properties of the labeled species are different from the corresponding properties of the unlabeled species. There are two different regimes: (a) If the deviations from neutrality are small, the response can be represented by a functional Taylor expansion; the terms of first order in the functional Taylor expansion correspond to the linear response law. (b) For large deviations, a phase linearization approach is more appropriate.
References
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13
Mini-Introduction to
Bioinformatics
There is enormous interest in the biology of complex reaction systems, be it in metabolism, signal transduction, gene regulatory networks, protein synthesis, and many others. The field of the interpretation of experiments on such systems by application of the methods of information science, computer science, and biostatistics is called bioinformatics (see [1] for a presentation of this subject). Part of it is an extension of the chemical approaches that we have discussed for obtaining information on the reaction mechanisms of complex chemical systems to complex biological and genetic systems. We present here a very brief introduction to this field, which is exploding with scientific and technical activity. No review is intended, only an indication of several approaches on the subject of our book, with apologies for the omission of vast numbers of publications.
A few reminders: The entire complement of DNA molecules constitute the genome, which consists of many genes. RNA is generated from DNA in a process called transcription; the RNA that codes for proteins is known as messenger RNA, abbreviated to mRNA. Other RNAs code for functional molecules such as transfer RNAs, ribosomal components, and regulatory molecules, or even have enzymatic function. Protein synthesis is regulated by many mechanisms, including that for transcription initiation, RNA splicing (in eukaryotes), mRNA transport, translation initiation, post-translational modifications, and degradation of mRNA. Proteins perform perhaps most cellular functions.
Advances in microarray technology, with the use of cDNA or oligonucleotides immobilized in a predefined organization on a solid phase, have led to measurements of mRNA expression levels on a genome-wide scale (see chapter 3). The results of the measurements can be displayed on a plot (fig. 13.1) on which a row represents one gene at various times, a column the whole set of genes, and the time of gene expression
207
Fig. 13.1 Clustering display of data from time course of expression by stimulation of primary human fibroblasts. See p. 209 for full caption.