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Titlebook: Research in Computational Molecular Biology; 11th Annunal Interna Terry Speed,Haiyan Huang Conference proceedings 2007 Springer-Verlag Berl

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书目名称Research in Computational Molecular Biology
副标题11th Annunal Interna
编辑Terry Speed,Haiyan Huang
视频videohttp://file.papertrans.cn/828/827950/827950.mp4
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Research in Computational Molecular Biology; 11th Annunal Interna Terry Speed,Haiyan Huang Conference proceedings 2007 Springer-Verlag Berl
出版日期Conference proceedings 2007
关键词DNA; DNA sequence motifs; Microarray; RNA; algorithms; bioinformatics; biology; computational biology; compu
版次1
doihttps://doi.org/10.1007/978-3-540-71681-5
isbn_softcover978-3-540-71680-8
isbn_ebook978-3-540-71681-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2007
The information of publication is updating

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Pairwise Global Alignment of Protein Interaction Networks by Matching Neighborhood Topology,e that the globally optimized alignment resolves ambiguity introduced by multiple local alignments. Finally, we interpret the results of global alignment to identify functional orthologs between yeast and fly; our functional ortholog prediction method is much simpler than a recently proposed approac
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Network Motif Discovery Using Subgraph Enumeration and Symmetry-Breaking,, our method enables us to study the clustering properties of discovered motifs, revealing even larger network elements..We apply this algorithm to the protein-protein interaction network and transcription regulatory network of ., and discover several large network motifs, which were previously inac
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Support Vector Training of Protein Alignment Models,gnment model learned by the SVM aligns 47% of the residues correctly and aligns over 70% of the residues within a shift of 4 positions.. Machine learning, Pairwise sequence alignment, Protein structure prediction.
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