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

TEMPO

書目名稱Research in Computational Molecular Biology影響因子(影響力)




書目名稱Research in Computational Molecular Biology影響因子(影響力)學(xué)科排名




書目名稱Research in Computational Molecular Biology網(wǎng)絡(luò)公開度




書目名稱Research in Computational Molecular Biology網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Research in Computational Molecular Biology被引頻次




書目名稱Research in Computational Molecular Biology被引頻次學(xué)科排名




書目名稱Research in Computational Molecular Biology年度引用




書目名稱Research in Computational Molecular Biology年度引用學(xué)科排名




書目名稱Research in Computational Molecular Biology讀者反饋




書目名稱Research in Computational Molecular Biology讀者反饋學(xué)科排名

中和

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

NICHE

infantile

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

Decrepit

合唱隊

ineluctable

URN

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.