| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_1c8cbbf2290b3f3a9988da29598baa2c |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N2015-1006
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N2015-1488
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N2015-1445
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N2021-638 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N15-1429
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N15-147
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N15-1475
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N21-63
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C12Q1-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N15-1434
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N21-64
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01J3-44
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B20-00 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N21-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N15-14
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N21-63
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N21-64
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01J3-44 |
| filingDate |
2018-06-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate |
2020-08-04-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_1f2ef4570ecd71a71b90e51c3f16a762
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_b837d9f34a41e407260f92beef5657b9 |
| publicationDate |
2020-08-04-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
US-10732092-B2 |
| titleOfInvention |
Analysis of single cell mechanical phenotyping for metastatic detection |
| abstract |
The present invention relates to a method and system for analyzing mechanical signatures of a plurality of cells for metastatic detection. Specifically, a data set characterized by at least one metric (such as Brillouin frequency shift and/or Brillouin linewidth) representing a cell mechanical signature is acquired for the plurality of cells by using a label-free Brillouin spectroscopy. A merit function is calculated based on one or more statistical characteristics of the data set, such as sensitivity and specificity. Then, the plurality of cells can be classified to detect metastatic cells based on mechanical signatures provided by the data set and an optimal metric value delivering maximum to the merit function. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2023175950-A1 |
| priorityDate |
2015-12-22-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |