Titlebook: Algorithms in Bioinformatics; 7th International Wo Raffaele Giancarlo,Sridhar Hannenhalli Conference proceedings 2007 Springer-Verlag Berli

muffler

Der aphasische Symptomenkomplex,d. A heuristic locally-optimal algorithm is given for founder construction. Combined with flat parsing this already gives quite good haplotyping results. Improved haplotyping is obtained by using a hierarchical parsing that properly models the natural recombination process. For finding short hierarc

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https://doi.org/10.1007/978-3-663-00191-1lyzing such complex models of evolution, investigate their computational complexity, and devise algorithms for solving them. Moreover, we demonstrate the viability of our methods on several synthetic datasets as well as biological datasets.

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agonist

https://doi.org/10.1007/978-3-663-09593-4two structures by measuring distance between their projected points. These methods offer a tremendous increase in speed over residue-level structural alignment methods. However, current projection methods are not practical, partly because they are unable to identify local similarities. We propose a

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顾客

Locality Kernels for Protein Classification,ur locality kernels measure protein sequence similarities within a small window constructed around matching amino acids. The kernels incorporate positional information of the amino acids inside the window and allow a range of position dependent similarity evaluations. We use these kernels with regul