| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_5caaefee7cb73a514a2b8bc29cf67b8a |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C12Y207-11024
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C07K2319-43
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B25-00 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B20-20
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B25-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B30-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B30-10
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-126
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C12N9-12
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C12N15-67
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C12Y207-11024
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/C07K14-43595
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16B40-20 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16B30-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16B20-00 |
| filingDate |
2018-07-25-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_d4aaf79f3289fda21450b5fcf60b5a75
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_0177bf0ccdce64a7082aa25a954a00ec
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_f75a640c178dd140316123b9a75a7783
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_825f20bb4ca2675daf48e9104a4a5857
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_d10b3c9a02de8d806262b903660d45d1 |
| publicationDate |
2021-01-28-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
US-2021027858-A1 |
| titleOfInvention |
Codon optimization method based on immune algorithm |
| abstract |
A codon optimization method based on an immune algorithm is characterized in that an immune algorithm and a genetic algorithm are successively used to respectively perform local multi-objective optimization and global multi-objective optimization on a protein coding sequence, and then an exhaustive method is used to perform fine adjustment and optimization on the sequence, so as to search the optimal expression sequence to the greatest extent. The present invention not only retains the characteristic of random global parallel search of the genetic algorithm, but also avoids premature convergence to a comparatively great extent to ensure rapid convergence to the global optimal solution. The present invention is the first to combine the advantages of the immune algorithm and the genetic algorithm in accuracy and efficiency to carry out codon optimization through a step-by-step process (local optimization, global optimization, and fine adjustment and optimization respectively in sequence), and proves the high efficiency of the algorithm in codon optimization through example tests. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-115440300-A |
| priorityDate |
2017-07-25-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |