Titlebook: Data Mining for Systems Biology; Methods and Protocol Hiroshi Mamitsuka Book 2018Latest edition Springer Science+Business Media, LLC, part

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書目名稱Data Mining for Systems Biology影響因子(影響力)




書目名稱Data Mining for Systems Biology影響因子(影響力)學(xué)科排名




書目名稱Data Mining for Systems Biology網(wǎng)絡(luò)公開度




書目名稱Data Mining for Systems Biology網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Data Mining for Systems Biology被引頻次




書目名稱Data Mining for Systems Biology被引頻次學(xué)科排名




書目名稱Data Mining for Systems Biology年度引用




書目名稱Data Mining for Systems Biology年度引用學(xué)科排名




書目名稱Data Mining for Systems Biology讀者反饋




書目名稱Data Mining for Systems Biology讀者反饋學(xué)科排名

教育學(xué)

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效果

正面

Inferring Antimicrobial Resistance from Pathogen Genomes in KEGG,ing an increasingly serious threat to the global public health. Here we present how knowledge on AMR is accumulated in the KEGG Pathogen resource and how such knowledge can be utilized by BlastKOALA and other web tools.

AUGUR

AUGUR

Commercial Aircraft Composite Technologyles analyzed by short read high-throughput sequencing. By grouping closely related strains together in clusters, the BIB pipeline is capable of estimating the relative abundances of the clusters contained in a sequencing sample.

非實體

https://doi.org/10.1007/978-3-319-31918-6. We provide a step-by-step guideline on how we trained the classification models and how it can easily generalize to user-defined reference genomes and specific applications. We also give additional details on what effect parameters in the algorithm have on performances.

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