TEMPO
发表于 2025-3-21 18:21:08
书目名称Research in Computational Molecular Biology影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0827950<br><br> <br><br>书目名称Research in Computational Molecular Biology影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0827950<br><br> <br><br>书目名称Research in Computational Molecular Biology网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0827950<br><br> <br><br>书目名称Research in Computational Molecular Biology网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0827950<br><br> <br><br>书目名称Research in Computational Molecular Biology被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0827950<br><br> <br><br>书目名称Research in Computational Molecular Biology被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0827950<br><br> <br><br>书目名称Research in Computational Molecular Biology年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0827950<br><br> <br><br>书目名称Research in Computational Molecular Biology年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0827950<br><br> <br><br>书目名称Research in Computational Molecular Biology读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0827950<br><br> <br><br>书目名称Research in Computational Molecular Biology读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0827950<br><br> <br><br>
中和
发表于 2025-3-21 20:29:15
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
Exclaim
发表于 2025-3-22 02:28:46
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NICHE
发表于 2025-3-22 06:42:57
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infantile
发表于 2025-3-22 11:31:55
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
vitreous-humor
发表于 2025-3-22 14:18:14
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Decrepit
发表于 2025-3-22 17:37:45
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合唱队
发表于 2025-3-22 23:52:20
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ineluctable
发表于 2025-3-23 05:08:47
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URN
发表于 2025-3-23 09:04:24
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.