33 resultados para Information in biology


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Novel computing systems are increasingly being composed of large numbers of heterogeneous components, each with potentially different goals or local perspectives, and connected in networks which change over time. Management of such systems quickly becomes infeasible for humans. As such, future computing systems should be able to achieve advanced levels of autonomous behaviour. In this context, the system's ability to be self-aware and be able to self-express becomes important. This paper surveys definitions and current understanding of self-awareness and self-expression in biology and cognitive science. Subsequently, previous efforts to apply these concepts to computing systems are described. This has enabled the development of novel working definitions for self-awareness and self-expression within the context of computing systems.

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Drawing on the newest findings of politeness research, this paper proposes an interactionally grounded approach to computer-mediated discourse (CMD). Through the analysis of naturally occurring text-based synchronous interactions of a virtual team the paper illustrates that the interactional politeness approach can account for linguistic phenomena not yet fully explored in computer-mediated discourse analysis. Strategies used for compensating for the lack of audio-visual information in computer-mediated communication, strategies to compensate for the technological constraints of the medium, and strategies to aid interaction management are examined from an interactional politeness viewpoint and compared to the previous findings of CMD analysis. The conclusion of this preliminary research suggests that the endeavour to communicate along the lines of politeness norms in a work-based virtual environment contradicts some of the previous findings of CMD research (unconventional orthography, capitalization, economizing), and that other areas (such as emoticons, backchannel signals and turn-taking strategies) need to be revisited and re-examined from an interactional perspective to fully understand how language functions in this merely text-based environment.

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DNA-binding proteins are crucial for various cellular processes and hence have become an important target for both basic research and drug development. With the avalanche of protein sequences generated in the postgenomic age, it is highly desired to establish an automated method for rapidly and accurately identifying DNA-binding proteins based on their sequence information alone. Owing to the fact that all biological species have developed beginning from a very limited number of ancestral species, it is important to take into account the evolutionary information in developing such a high-throughput tool. In view of this, a new predictor was proposed by incorporating the evolutionary information into the general form of pseudo amino acid composition via the top-n-gram approach. It was observed by comparing the new predictor with the existing methods via both jackknife test and independent data-set test that the new predictor outperformed its counterparts. It is anticipated that the new predictor may become a useful vehicle for identifying DNA-binding proteins. It has not escaped our notice that the novel approach to extract evolutionary information into the formulation of statistical samples can be used to identify many other protein attributes as well.