Titlebook: Web Log Mining als Instrument der Marketingforschung; Ein systemgestaltend Frank Bensberg Book 2001 Springer Fachmedien Wiesbaden 2001 Cont

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Frank Bensbergare close to experimental results (where measured). It will be further refined as values of the parameters are determined experimentally. The model was developed in Systems Biology Markup Language (SBML) and it is available from the authors and from the Biomodels repository [www.ebi.ac.uk/biomodels].

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experiments in a university, whose results have demonstrated that our system makes the creation of attractive animations easier and faster (only about 10 % operation time) than manual creation of equal quality, and it is effective to use embodied agents in education applications.

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Frank Bensbergs is to draw inspiration from biology, as in autonomic computing, in order to achieve an efficient and robust communication system. This requires a multi-disciplinary approach to ICT-related research, which in our view can lead to innovative and creative solutions to the challenges related to next generation networks.

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from PubMed, are constructed based on the methodology (http://ginni.bme.ntu.edu.tw). The hierarchical presentation of clustering results and the interactive graphical display of the contents of each cluster shows the merits of our approach.

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Frank Bensbergopments of computational methods for the prediction of protein interactions based on genome and sequence information, and the development of databases and standards that facilitate the analysis of all this information.

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Frank Bensbergen compared with other popular algorithms. In most real cases, our algorithm gives the same haplotyping results but runs much faster. In some real cases, other algorithms give an answer which has the least number of recombinations, while our algorithm gives a more credible solution and runs faster.

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Frank Bensbergnner more multi-disciplinary efforts such as ours would be of significant benefit to this research area [20]. This paper might be viewed as an advert for the benefits of multi-disciplinary teams in understanding new experimental data in medicine and biology.