http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112289373-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B30-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B20-00 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16B20-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16B30-00 |
| filingDate | 2020-10-27-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2021-07-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2021-07-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-112289373-B |
| titleOfInvention | lncRNA-miRNA-disease association method fusing similarity |
| abstract | The invention discloses a lncRNA-miRNA-disease association method fusing similarity, which comprises the following steps: constructing an lncRNA-miRNA-disease network; calculating the functional similarity of the fused lncRNA; calculating integrated disease semantic similarity; obtaining a weight matrix of miRNA between miRNA-lncRNA and a weight matrix of miRNA between miRNA-diseases according to a weight distribution algorithm; obtaining a miRNA-lncRNA association score matrix from the fused lncRNA with similar functions, the miRNA-lncRNA adjacency matrix and the miRNA weight matrix between the miRNA-lncRNA; integrating miRNA weight matrixes among disease semantic similarity, miRNA-disease adjacency matrixes and miRNA-disease matrixes to obtain miRNA-disease association score matrixes; integrating the two correlation matrixes to obtain a correlation score matrix S mld (ii) a Using a predictive model pair S mld And (6) performing prediction. The invention discloses an unknown association relationship hidden under data through a multi-aspect data relationship. |
| priorityDate | 2020-10-27-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 17.