Method for targeting transcriptionally active loci


Ontology type: sgo:Patent     


Patent Info

DATE

N/A

AUTHORS

Aris N. Economides , Thomas M. DeChiara , George D. Yancopoulos

ABSTRACT

The present invention provides a method of achieving very high targeting efficiency by utilizing targeting vectors that utilize promoter-less selection cassettes and which are engineered to targeted into transcriptionally active loci. In particular, the invention provides a method for targeting promoter-less selection cassettes into transcriptionally active loci in stem cells or other eukaryotic cells with much greater efficiency than previously observed with other methods, thus reducing the number of drug-resistant clones to be screened or eliminating the need to screen for targeted cells altogether. The invention also encompasses the DNA targeting vectors, the targeted cells, as well as non-human organisms, especially mice, created from the targeted cells. More... »

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/2620", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "name": "Aris N. Economides", 
        "type": "Person"
      }, 
      {
        "name": "Thomas M. DeChiara", 
        "type": "Person"
      }, 
      {
        "name": "George D. Yancopoulos", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1093/embo-reports/kve064", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013276747"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.96.3.797", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027804450"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.91.10.4303", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027954179"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/5007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030839891", 
          "https://doi.org/10.1038/5007"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02369894", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045426532", 
          "https://doi.org/10.1007/bf02369894"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01969118", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047407479", 
          "https://doi.org/10.1007/bf01969118"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "description": "

The present invention provides a method of achieving very high targeting efficiency by utilizing targeting vectors that utilize promoter-less selection cassettes and which are engineered to targeted into transcriptionally active loci. In particular, the invention provides a method for targeting promoter-less selection cassettes into transcriptionally active loci in stem cells or other eukaryotic cells with much greater efficiency than previously observed with other methods, thus reducing the number of drug-resistant clones to be screened or eliminating the need to screen for targeted cells altogether. The invention also encompasses the DNA targeting vectors, the targeted cells, as well as non-human organisms, especially mice, created from the targeted cells.

", "id": "sg:patent.US-7473557-B2", "keywords": [ "method", "locus", "invention", "efficiency", "vector", "selection", "stem cell", "eukaryotic cell", "great efficiency", "resistant clone", "screen", "targeted cell", "Targeting", "human organism", "mouse" ], "name": "Method for targeting transcriptionally active loci", "recipient": [ { "id": "https://www.grid.ac/institutes/grid.418961.3", "type": "Organization" } ], "sameAs": [ "https://app.dimensions.ai/details/patent/US-7473557-B2" ], "sdDataset": "patents", "sdDatePublished": "2019-03-07T15:32", "sdLicense": "https://scigraph.springernature.com/explorer/license/", "sdPublisher": { "name": "Springer Nature - SN SciGraph project", "type": "Organization" }, "sdSource": "s3://com.uberresearch.data.dev.patents-pipeline/full_run_10/sn-export/5eb3e5a348d7f117b22cc85fb0b02730/0000100128-0000348334/json_export_1a463c9e.jsonl", "type": "Patent" } ]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/patent.US-7473557-B2'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/patent.US-7473557-B2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/patent.US-7473557-B2'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/patent.US-7473557-B2'


 

This table displays all metadata directly associated to this object as RDF triples.

65 TRIPLES      14 PREDICATES      34 URIs      22 LITERALS      2 BLANK NODES

Subject Predicate Object
1 sg:patent.US-7473557-B2 schema:about anzsrc-for:2620
2 schema:author N32085c88129541e288c3bc95dca7bdc6
3 schema:citation sg:pub.10.1007/bf01969118
4 sg:pub.10.1007/bf02369894
5 sg:pub.10.1038/5007
6 https://doi.org/10.1073/pnas.91.10.4303
7 https://doi.org/10.1073/pnas.96.3.797
8 https://doi.org/10.1093/embo-reports/kve064
9 schema:description <p num="p-0001">The present invention provides a method of achieving very high targeting efficiency by utilizing targeting vectors that utilize promoter-less selection cassettes and which are engineered to targeted into transcriptionally active loci. In particular, the invention provides a method for targeting promoter-less selection cassettes into transcriptionally active loci in stem cells or other eukaryotic cells with much greater efficiency than previously observed with other methods, thus reducing the number of drug-resistant clones to be screened or eliminating the need to screen for targeted cells altogether. The invention also encompasses the DNA targeting vectors, the targeted cells, as well as non-human organisms, especially mice, created from the targeted cells.</p>
10 schema:keywords Targeting
11 efficiency
12 eukaryotic cell
13 great efficiency
14 human organism
15 invention
16 locus
17 method
18 mouse
19 resistant clone
20 screen
21 selection
22 stem cell
23 targeted cell
24 vector
25 schema:name Method for targeting transcriptionally active loci
26 schema:recipient https://www.grid.ac/institutes/grid.418961.3
27 schema:sameAs https://app.dimensions.ai/details/patent/US-7473557-B2
28 schema:sdDatePublished 2019-03-07T15:32
29 schema:sdLicense https://scigraph.springernature.com/explorer/license/
30 schema:sdPublisher N1de03ecfd6f748d5a60485fe61f9f936
31 sgo:license sg:explorer/license/
32 sgo:sdDataset patents
33 rdf:type sgo:Patent
34 N1de03ecfd6f748d5a60485fe61f9f936 schema:name Springer Nature - SN SciGraph project
35 rdf:type schema:Organization
36 N2210ba56896743b29f951b07c0f35ea8 schema:name Aris N. Economides
37 rdf:type schema:Person
38 N2eabb4ac8244421fbd9f9747db2d01e2 rdf:first N7b5ea8e547444de4a40d264acb16975e
39 rdf:rest Nb9d315979bff4be7b20ed7e36b7687ef
40 N32085c88129541e288c3bc95dca7bdc6 rdf:first N2210ba56896743b29f951b07c0f35ea8
41 rdf:rest N2eabb4ac8244421fbd9f9747db2d01e2
42 N7b5ea8e547444de4a40d264acb16975e schema:name Thomas M. DeChiara
43 rdf:type schema:Person
44 N84df232d3a164f2f8c423f39f67c60f2 schema:name George D. Yancopoulos
45 rdf:type schema:Person
46 Nb9d315979bff4be7b20ed7e36b7687ef rdf:first N84df232d3a164f2f8c423f39f67c60f2
47 rdf:rest rdf:nil
48 anzsrc-for:2620 schema:inDefinedTermSet anzsrc-for:
49 rdf:type schema:DefinedTerm
50 sg:pub.10.1007/bf01969118 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047407479
51 https://doi.org/10.1007/bf01969118
52 rdf:type schema:CreativeWork
53 sg:pub.10.1007/bf02369894 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045426532
54 https://doi.org/10.1007/bf02369894
55 rdf:type schema:CreativeWork
56 sg:pub.10.1038/5007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030839891
57 https://doi.org/10.1038/5007
58 rdf:type schema:CreativeWork
59 https://doi.org/10.1073/pnas.91.10.4303 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027954179
60 rdf:type schema:CreativeWork
61 https://doi.org/10.1073/pnas.96.3.797 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027804450
62 rdf:type schema:CreativeWork
63 https://doi.org/10.1093/embo-reports/kve064 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013276747
64 rdf:type schema:CreativeWork
65 https://www.grid.ac/institutes/grid.418961.3 schema:Organization
 




Preview window. Press ESC to close (or click here)


...