Titlebook: Data Mining for Systems Biology; Methods and Protocol Hiroshi Mamitsuka,Charles DeLisi,Minoru Kanehisa Book 2013 Springer Science+Business

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书目名称Data Mining for Systems Biology影响因子(影响力)学科排名




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书目名称Data Mining for Systems Biology网络公开度学科排名




书目名称Data Mining for Systems Biology被引频次




书目名称Data Mining for Systems Biology被引频次学科排名




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书目名称Data Mining for Systems Biology年度引用学科排名




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书目名称Data Mining for Systems Biology读者反馈学科排名

哀求

,Discovering Interacting Domains and Motifs in Protein–Protein Interactions,o stimuli. These interactions are usually transient, easily formed, and disrupted, yet specific. Many of these transient interactions involve the binding of a protein domain to a short stretch (3–10) of amino acid residues, which can be characterized by a sequence pattern, i.e., .. We call these int

凶兆

Anthrp

MILL

敲竹杠

Mining Regulatory Network Connections by Ranking Transcription Factor Target Genes Using Time Serieunderlying network. We present a technique addressing this problem through focussing on a more limited problem: inferring direct targets of a transcription factor from short expression time series. The method is based on combining Gaussian process priors and ordinary differential equation models all

敲竹杠

青少年

Mining Frequent Subtrees in Glycan Data Using the Rings Glycan Miner Tool, the α-closed frequent subtree algorithm to find significant subtrees from within a data set of glycan structures, or carbohydrate sugar chains. The results are returned in order of .-value, which is computed based on the probability of the reproducibility of the returned structures. There is also a

废除

Fantasy

Localization Prediction and Structure-Based In Silico Analysis of Bacterial Proteins: With Emphasis focus on β-barrel outer membrane proteins (BOMPs), describing and evaluating new tools for BOMP detection and topology prediction. Finally, we apply general protein structure prediction methods on these proteins to show that the structure of most BOMPs in . can be modeled reliably.