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Titlebook: Bioinformatics Research and Applications; Third International Ion M?ndoiu,Alexander Zelikovsky Conference proceedings 2007 Springer-Verlag

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樓主: 紀念性
31#
發(fā)表于 2025-3-26 20:56:38 | 只看該作者
,Die logische Struktur kausaler Erkl?rungen,rk we characterized the existence of the galled-tree networks. Building on this, we present a polynomial algorithm for haplotyping via galled-tree networks with simple galls (having two mutations). In the end, we give the experimental results comparing our algorithm with PHASE on simulated data.
32#
發(fā)表于 2025-3-27 04:08:37 | 只看該作者
Kausalmodellierung mit Partial Least Squares that can exploit such structured graphical nature. Finally, we compare our approach against a specific flat list method by analyzing the cdc15-subset of the well known Spellman’s Yeast Cell Cycle dataset [2].
33#
發(fā)表于 2025-3-27 06:12:41 | 只看該作者
34#
發(fā)表于 2025-3-27 12:40:27 | 只看該作者
Efficiently Finding the Most Parsimonious Phylogenetic Tree Via Linear Programming,provably efficient methods. The program solves several large mtDNA and Y-chromosome instances within a few seconds, giving provably optimal results in times competitive with fast heuristics than cannot guarantee optimality.
35#
發(fā)表于 2025-3-27 15:18:02 | 只看該作者
36#
發(fā)表于 2025-3-27 20:21:28 | 只看該作者
37#
發(fā)表于 2025-3-28 00:21:26 | 只看該作者
38#
發(fā)表于 2025-3-28 04:35:08 | 只看該作者
39#
發(fā)表于 2025-3-28 06:50:03 | 只看該作者
Algorithm for Haplotype Inferring Via Galled-Tree Networks with Simple Galls,rk we characterized the existence of the galled-tree networks. Building on this, we present a polynomial algorithm for haplotyping via galled-tree networks with simple galls (having two mutations). In the end, we give the experimental results comparing our algorithm with PHASE on simulated data.
40#
發(fā)表于 2025-3-28 14:22:58 | 只看該作者
Discovering Relations Among GO-Annotated Clusters by Graph Kernel Methods, that can exploit such structured graphical nature. Finally, we compare our approach against a specific flat list method by analyzing the cdc15-subset of the well known Spellman’s Yeast Cell Cycle dataset [2].
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