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Titlebook: Biocomputing; Panos M. Pardalos,Jose Principe Book 20021st edition Kluwer Academic Publishers 2002 algorithms.approximation algorithm.calc

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楼主: Carter
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,Hinführung und thematische Einbettung,ry, non-Gaussian, asynchronous, noisy, and unpredictable in fine grain, yet undeniably they are among the most successful devices that a billion years of evolution has produced. No one can justifiably claim that he or she has modeled brains, but they are a flowing spring of new concepts, and they pr
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Diskussion und Transfer der Ergebnisse,al chemists, and on the other by biologists and organic chemists. These two group are both interested in how computation can help us better understand biological systems. The motivation for joining the two cultures is heightened by the growth of genomic sequence databases, which add greatly to the a
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https://doi.org/10.1007/978-3-8349-8452-4t modifications the algorithm has been implemented in the ZINDO program package, and has proven to require less computer time than other procedures that demand the full evaluation of the Hessian. We demonstrate that this procedure is able to give a good approximation of the minimum energy reaction p
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Design in der Natur und nach der Naturven a set of . positively weighted axis parallel rectangles such that, for each axis, the projection of a rectangle on this axis does not enclose that of another, and our goal is to select a subset of . rectangles from the given set of rectangles of total maximum weight, where two rectangles are ind
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https://doi.org/10.1007/978-3-642-60292-4measures are employed to estimate the difference between two data distributions, obtained by segmenting the voxel time series based on the experimental protocol time-line. In order to validate the new technique activation signals were acquired from a specially constructed dynamic fMRI phantom placed
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Kreativität und Innovation: Gegensätze?dering the velocity of an incompressible fluid. Conversely, locations where energy is not conserved are sources or sinks. In this paper we show how sources and sinks connect two disparate problems of interest in medical image analysis: the computation of skeletons and the segmentation of tubular str
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