Computer Science
Hidden Markov Models
100%
Support Vector Machine
100%
Machine Learning
50%
Extracted Information
50%
Random Decision Forest
50%
Annotation
50%
Information Sequence
50%
Surrounding Region
50%
False Negative
50%
Classification Performance
50%
Classification Task
50%
False Positive Rate
50%
Domain Knowledge
50%
Prediction Error
50%
Biochemistry, Genetics and Molecular Biology
DNA Sequence
100%
Hidden Markov Model
66%
Discrimination Learning
66%
Support Vector Machine
66%
Polyadenylation
33%
Genome Annotation
33%
Dynamics
33%
Messenger RNA
33%
Random Forest
33%
Position
33%
Nucleotide Sequence
33%
Sequence Motif
33%
Kernel Method
33%
Keyphrases
Latent Feature
100%
Generative Learning
28%
Discriminative Learning
28%
Poly(A) Tail
28%
Genome Annotation
14%
Spectral Algorithms
14%
False Negative Rate
14%
Novel Machine
14%
Error Prediction
14%
Feature Engineering
14%
Statistical Thermodynamics
14%
String Kernel
14%
Learning Support
14%
Manual Features
14%
DNA Sequence Motifs
14%
Depth Domain
14%
Model Learning
14%
Chemistry
DNA Sequence
100%
Nucleotide Sequence
33%
Number
33%
Messenger RNA
33%
Oligomer
33%
Material Science
DNA Sequence
100%
Hidden Markov Models
66%