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Predicting class II MHC-Peptide binding: a kernel based approach using similarity scores
Jesper Salomon, Darren R. Flower
Aston Pharmacy School
College of Health and Life Sciences
Aston Research Centre for Health in Ageing
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peer-review
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Dive into the research topics of 'Predicting class II MHC-Peptide binding: a kernel based approach using similarity scores'. Together they form a unique fingerprint.
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Mathematics
Major Histocompatibility Complex
100%
Peptides
76%
Similarity
45%
kernel
36%
Class
15%
Background Modeling
12%
Prediction
10%
Knowledge-based
9%
Amino Acids
8%
T-cells
8%
Modeling Method
8%
Kernel Methods
7%
Alignment
7%
Cross-validation
7%
Ambiguity
7%
Molecules
6%
Uncertainty
5%
Evaluation
4%
Interaction
4%
Testing
4%
Modeling
4%
Performance
3%
Medicine & Life Sciences
Major Histocompatibility Complex
55%
Peptides
34%
Alleles
14%
Datasets
10%
T-Lymphocyte Epitopes
8%
Uncertainty
6%
Amino Acids
4%
Databases
4%
Engineering & Materials Science
Peptides
71%
Epitopes
10%
T-cells
10%
Amino acids
8%
Molecules
6%
Binders
6%
Uncertainty
4%
Testing
3%
Chemistry
Peptide
31%
Length
8%
Epitope
6%
Binding Agent
5%
Acid
2%
Molecule
2%