http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111370072-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C20-70 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/H01J49-0036 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B45-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-02 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C20-80 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C20-70 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B40-10 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N27-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C20-80 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16C20-20 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16C20-80 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16C20-70 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16C20-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N27-62 |
| filingDate | 2020-03-04-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2020-11-17-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2020-11-17-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-111370072-B |
| titleOfInvention | Implementation method of molecular omics data structure based on data-independent acquisition of mass spectrometry |
| abstract | The invention relates to the technical field of biomolecular omics mass spectrometry data, in particular to a method for realizing a molecular omics data structure based on data-independent acquisition of mass spectrometry. The attributes of each dimension, the first dimension is the index of cycle times, the second dimension is the fragment ion mass-to-charge ratio, and the third dimension is the precursor ion window index corresponding to the fragment ion. The DIAT tensor data described in this case has high integrity, is easy to read and has a fast reading speed. The size of the DIAT file is only a few tenths of that of the mzXML file. The DIAT file image can be directly observed by visualizing the pooled DIAT file image. , can directly use the visual processing algorithm to analyze the DIAT tensor, avoid the operation of extracting ion chromatographic peaks with a large amount of calculation, and can directly establish a computer deep learning model for clinical sample classification based on this file. |
| priorityDate | 2020-03-04-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 26.