http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112002374-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B40-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B15-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B20-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16B40-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16B15-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16B20-30 |
| filingDate | 2020-06-14-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2022-04-22-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2022-04-22-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-112002374-B |
| titleOfInvention | MHC-I epitope affinity prediction method based on deep learning |
| abstract | The present invention discloses a method for predicting the affinity of MHC-I epitope based on deep learning, which comprises: obtaining a plurality of polypeptides through a public database; converting the polypeptides into 21mer peptides according to the binding mode of MHC-I molecules and peptides; The characteristics of the polypeptide include: sequence characteristics, hydrophilic characteristics, polarity characteristics and position characteristics; the characteristics of the polypeptide are encoded separately to obtain a 4*21-dimensional characteristic matrix; the public database The polypeptide data in the model is used as a training set for model training. According to the classification of alleles of the polypeptide, the feature matrix of the polypeptide is input into the pre-established CNN model to establish a prediction model, and the number of established prediction models is the same as that of the polypeptide. Binding affinity test was performed using the polypeptide data of the public database as the validation set of the prediction model. The present application can effectively predict the affinity of the MHC-I epitope, and the prediction accuracy is higher and more stable. |
| priorityDate | 2020-06-14-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 24.