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Titlebook: Algorithms in Bioinformatics; 11th International W Teresa M. Przytycka,Marie-France Sagot Conference proceedings 2011 Springer-Verlag GmbH

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樓主: 氣泡
61#
發(fā)表于 2025-4-1 05:48:32 | 只看該作者
Graph-Based Decomposition of Biochemical Reaction Networks into Monotone Subsystems,n to a medium-scale model for signaling pathways in yeast demonstrates that our algorithm yields efficient and biologically interpretable modularizations; both aspects are critical for extending the scope of (quantitative) cellular network analysis.
62#
發(fā)表于 2025-4-1 06:26:47 | 只看該作者
63#
發(fā)表于 2025-4-1 12:00:32 | 只看該作者
K?lner Beitr?ge zur Didaktik der Mathematikes, and consider the optimization problem of removing the minimum number of leaves leading to a tree without any NAD vertex. We develop a polynomial-time algorithm that is exact for two special classes of gene trees, and show a good performance on simulated data sets in the general case.
64#
發(fā)表于 2025-4-1 15:26:33 | 只看該作者
Empirische Befunde: Forschungsprodukteng classifier that optimally combines a set of PWMs and chrommosal position based classifiers. This non-linear binding decision rule drastically reduces the rate of false positives so that .?consistently outperforms sequence-based methods. This is shown by implementing a cross-validation analysis in
65#
發(fā)表于 2025-4-1 21:26:03 | 只看該作者
https://doi.org/10.1007/978-3-642-91769-1n to a medium-scale model for signaling pathways in yeast demonstrates that our algorithm yields efficient and biologically interpretable modularizations; both aspects are critical for extending the scope of (quantitative) cellular network analysis.
66#
發(fā)表于 2025-4-2 00:58:22 | 只看該作者
Die gemeinsamen Forderungen der Zementnormenf distance-based phylogenetic inference from whole-genome data; our approach combines features of the jackknife and the bootstrap and remains nonparametric. For each feature of our method, we give an equivalent feature in the sequence-based framework; we also present the results of extensive experim
67#
發(fā)表于 2025-4-2 02:51:43 | 只看該作者
Automated Segmentation of DNA Sequences with Complex Evolutionary Histories,equences of predetermined markers, for example protein coding genes or other functional elements. However, markers defined in this way ignore information included in non-coding sequences, are prone to errors in annotation, and may even introduce artifacts due to partial gene copies or chimeric genes
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