http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-106485096-B
Outgoing Links
Predicate | Object |
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classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B20-00 |
classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16B25-10 |
filingDate | 2016-10-20-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
grantDate | 2019-03-26-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
publicationDate | 2019-03-26-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
publicationNumber | CN-106485096-B |
titleOfInvention | The miRNA- Relationship To Environmental Factors prediction technique learnt based on random two-way migration and multi-tag |
abstract | The invention discloses a kind of miRNA- Relationship To Environmental Factors prediction techniques learnt based on random two-way migration and multi-tag.It is imperfect in view of single biological data, the similitude of miRNA and environmental factor is calculated separately using different biological datas and different method for measuring similarity.In addition, present invention introduces similarity matrix fusion methods in order to reduce single similarity measurement noise to improve final miRNA and environmental factor similitude reliability.On this basis, potential miRNA- Relationship To Environmental Factors are predicted using random two-way migration algorithm and multi-tag learning method.The present invention is simple and effective, by the way that test shows that the invention has preferable estimated performance in terms of the potential relationship of miRNA- environmental factor compared with other methods, and on given data collection.Analysis of cases shows the present invention it can be found that some potential environmental factors correspond to miRNA, and the further experiment that can carry out the discovery of miRNA- environmental factor for biologist provides valuable reference information. |
priorityDate | 2016-10-20-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 650.