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Whole-genome based bacterial phenotype predictions with machine learning.
Signe Tang Karlsen
Research Group for Genomic Epidemiology
National Food Institute
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Ph.D. thesis
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Dive into the research topics of 'Whole-genome based bacterial phenotype predictions with machine learning.'. Together they form a unique fingerprint.
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Keyphrases
Whole Genome
100%
Machine Learning
100%
Bacterial Phenotype
100%
Phenotype Prediction
100%
Sustainable Alternatives
66%
Lactococcus Lactis
33%
Agriculture
33%
Pathogenic Bacteria
33%
Bacillus
33%
Computational Methods
33%
Cheese
33%
Genome Sequencing
33%
Bacterial Strains
33%
Livestock
33%
Growth Factors
33%
Animal Health
33%
Antibiotic Use
33%
Fermented Foods
33%
High Diversity
33%
Functional Variation
33%
Machine Learning Models
33%
Plant Health
33%
Genomic Elements
33%
Chemical Pesticides
33%
Diversity Variation
33%
Biased Data
33%
Hypothesis-driven Approach
33%
Immunology and Microbiology
Bacilli
100%
Lactococcus Lactis
100%
Bacterial Strain
100%
Animal Health
100%
Food Science
Lactococcus
100%
Fermented Food
100%