Predicate |
Object |
assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_3cf20948abcac064355cf0f70264a885 |
classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B50-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B20-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B30-10 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-00 |
classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16B50-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N20-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16B30-10 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16B20-20 |
filingDate |
2020-09-21-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
grantDate |
2021-01-19-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_e6d0a1a66a92abbc8ce7bf7447a1426f http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_3d4e7046a81911a8b089b0cb80866c19 |
publicationDate |
2021-01-19-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
publicationNumber |
KR-102204509-B1 |
titleOfInvention |
System for pathogenicity prediction of genomic mutation using machine learning |
abstract |
The present invention learns the first fusion data in which genetically mutated protein sequence data and evolutionary conservation data are fused, and the second fusion data in which natural state protein sequence data and evolutionary conservation data are fused through an artificial neural network (ANN). Provides a system for predicting pathogenicity of genetic mutations using machine learning to determine whether genetic mutations are pathogenic. |
isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2022059886-A1 http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2022245042-A1 |
priorityDate |
2020-09-21-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
type |
http://data.epo.org/linked-data/def/patent/Publication |