Titlebook: Machine Learning for Microbial Phenotype Prediction; Roman Feldbauer Book 2016 The Editor(s) (if applicable) and The Author(s), under excl

他剪短

書目名稱Machine Learning for Microbial Phenotype Prediction影響因子(影響力)




書目名稱Machine Learning for Microbial Phenotype Prediction影響因子(影響力)學(xué)科排名




書目名稱Machine Learning for Microbial Phenotype Prediction網(wǎng)絡(luò)公開度




書目名稱Machine Learning for Microbial Phenotype Prediction網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Machine Learning for Microbial Phenotype Prediction被引頻次




書目名稱Machine Learning for Microbial Phenotype Prediction被引頻次學(xué)科排名




書目名稱Machine Learning for Microbial Phenotype Prediction年度引用




書目名稱Machine Learning for Microbial Phenotype Prediction年度引用學(xué)科排名




書目名稱Machine Learning for Microbial Phenotype Prediction讀者反饋




書目名稱Machine Learning for Microbial Phenotype Prediction讀者反饋學(xué)科排名

cutlery

patriarch

2625-3577 microbial phenotype prediction based on supervised machine learning, several models for biological and ecological traits of high relevance, and the deployment in metagenomic datasets. The results suggest that the presented prediction tool can be used to automatically annotate phenotypes in near-comp

palpitate

征服

2625-3577 netic information and its observable traits is a central biological problem. Phenotype prediction facilitated by machine learning techniques will be a major step forward to creating biological knowledge from big data.978-3-658-14318-3978-3-658-14319-0Series ISSN 2625-3577 Series E-ISSN 2625-3615

Kaleidoscope

Book 2016. Unraveling relationships between a living organism‘s genetic information and its observable traits is a central biological problem. Phenotype prediction facilitated by machine learning techniques will be a major step forward to creating biological knowledge from big data.

MEN

眨眼

https://doi.org/10.1007/978-3-658-14319-0bioinformatics; microorganisms; metagenomics; genotype; classification

ARM

978-3-658-14318-3The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wies

消瘦