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Towards
in silico
prediction of immunogenic epitopes
Darren R. Flower
Aston Pharmacy School
College of Health and Life Sciences
Aston Research Centre for Health in Ageing
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in silico
prediction of immunogenic epitopes'. Together they form a unique fingerprint.
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Keyphrases
3D Protein Structure
50%
Artificial Intelligence
50%
Bacterial Genomes
50%
Bioinformatic Prediction
50%
Development Data
50%
Epitope Prediction
100%
Hope for the Future
50%
Immunogenic Epitopes
100%
In Silico Methods
50%
In Silico Prediction
100%
Inconsistent Results
50%
Molecular Modeling Methods
50%
Prediction Model
50%
Prediction Rate
50%
Recognition Process
50%
Sequence-based Methods
50%
Torrent
50%
Biochemistry, Genetics and Molecular Biology
Artificial Intelligence
100%
Bioinformatics
100%
Hope
100%
Immunity
100%
Microbial Genomics
100%
Molecular Model
100%
Protein Structure
100%
Medicine and Dentistry
Epitope
100%
Hope
25%
Immunity
25%
In Silico
100%
Microbial Genomics
25%
Molecular Model
25%
Protein Structure
25%
Food Science
Protein Structure
100%