Network motifs in the transcriptional regulation network of Escherichia coli View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2002-04-22

AUTHORS

Shai S. Shen-Orr, Ron Milo, Shmoolik Mangan, Uri Alon

ABSTRACT

Little is known about the design principles1,2,3,4,5,6,7,8,9,10 of transcriptional regulation networks that control gene expression in cells. Recent advances in data collection and analysis2,11,12, however, are generating unprecedented amounts of information about gene regulation networks. To understand these complex wiring diagrams1,2,3,4,5,6,7,8,9,10,13, we sought to break down such networks into basic building blocks2. We generalize the notion of motifs, widely used for sequence analysis, to the level of networks. We define 'network motifs' as patterns of interconnections that recur in many different parts of a network at frequencies much higher than those found in randomized networks. We applied new algorithms for systematically detecting network motifs to one of the best-characterized regulation networks, that of direct transcriptional interactions in Escherichia coli3,6. We find that much of the network is composed of repeated appearances of three highly significant motifs. Each network motif has a specific function in determining gene expression, such as generating temporal expression programs and governing the responses to fluctuating external signals. The motif structure also allows an easily interpretable view of the entire known transcriptional network of the organism. This approach may help define the basic computational elements of other biological networks. More... »

PAGES

64-68

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/ng881

DOI

http://dx.doi.org/10.1038/ng881

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1010954918

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/11967538


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

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/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Genetics", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Algorithms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Databases, Genetic", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Escherichia coli", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Gene Expression Regulation, Bacterial", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Genes, Bacterial", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Genetic", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Regulon", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Signal Transduction", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Transcription Factors", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Transcription, Genetic", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Molecular Cell Biology, Weizmann Institute of Science, 76100, Rehovot, Israel", 
          "id": "http://www.grid.ac/institutes/grid.13992.30", 
          "name": [
            "Department of Molecular Cell Biology, Weizmann Institute of Science, 76100, Rehovot, Israel"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shen-Orr", 
        "givenName": "Shai S.", 
        "id": "sg:person.01213007720.49", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213007720.49"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Physics of Complex Systems, Weizmann Institute of Science, 76100, Rehovot, Israel", 
          "id": "http://www.grid.ac/institutes/grid.13992.30", 
          "name": [
            "Department of Physics of Complex Systems, Weizmann Institute of Science, 76100, Rehovot, Israel"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Milo", 
        "givenName": "Ron", 
        "id": "sg:person.0774352340.01", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0774352340.01"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Molecular Cell Biology, Weizmann Institute of Science, 76100, Rehovot, Israel", 
          "id": "http://www.grid.ac/institutes/grid.13992.30", 
          "name": [
            "Department of Molecular Cell Biology, Weizmann Institute of Science, 76100, Rehovot, Israel"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mangan", 
        "givenName": "Shmoolik", 
        "id": "sg:person.016437275623.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016437275623.42"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Physics of Complex Systems, Weizmann Institute of Science, 76100, Rehovot, Israel", 
          "id": "http://www.grid.ac/institutes/grid.13992.30", 
          "name": [
            "Department of Molecular Cell Biology, Weizmann Institute of Science, 76100, Rehovot, Israel", 
            "Department of Physics of Complex Systems, Weizmann Institute of Science, 76100, Rehovot, Israel"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Alon", 
        "givenName": "Uri", 
        "id": "sg:person.01310216122.13", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01310216122.13"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/35036627", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051510804", 
          "https://doi.org/10.1038/35036627"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35065725", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005249327", 
          "https://doi.org/10.1038/35065725"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35011540", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019498862", 
          "https://doi.org/10.1038/35011540"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/376307a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044112594", 
          "https://doi.org/10.1038/376307a0"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2002-04-22", 
    "datePublishedReg": "2002-04-22", 
    "description": "Little is known about the design principles1,2,3,4,5,6,7,8,9,10 of transcriptional regulation networks that control gene expression in cells. Recent advances in data collection and analysis2,11,12, however, are generating unprecedented amounts of information about gene regulation networks. To understand these complex wiring diagrams1,2,3,4,5,6,7,8,9,10,13, we sought to break down such networks into basic building blocks2. We generalize the notion of motifs, widely used for sequence analysis, to the level of networks. We define 'network motifs' as patterns of interconnections that recur in many different parts of a network at frequencies much higher than those found in randomized networks. We applied new algorithms for systematically detecting network motifs to one of the best-characterized regulation networks, that of direct transcriptional interactions in Escherichia coli3,6. We find that much of the network is composed of repeated appearances of three highly significant motifs. Each network motif has a specific function in determining gene expression, such as generating temporal expression programs and governing the responses to fluctuating external signals. The motif structure also allows an easily interpretable view of the entire known transcriptional network of the organism. This approach may help define the basic computational elements of other biological networks.", 
    "genre": "article", 
    "id": "sg:pub.10.1038/ng881", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1103138", 
        "issn": [
          "1061-4036", 
          "1546-1718"
        ], 
        "name": "Nature Genetics", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "31"
      }
    ], 
    "keywords": [
      "transcriptional regulation network", 
      "regulation network", 
      "network motifs", 
      "gene expression", 
      "direct transcriptional interactions", 
      "gene regulation networks", 
      "expression programs", 
      "transcriptional networks", 
      "transcriptional interactions", 
      "sequence analysis", 
      "motif structure", 
      "external signals", 
      "Escherichia coli", 
      "specific functions", 
      "biological networks", 
      "motif", 
      "interpretable view", 
      "significant motifs", 
      "expression", 
      "recent advances", 
      "notion of motif", 
      "randomized networks", 
      "unprecedented amount", 
      "pattern of interconnections", 
      "organisms", 
      "coli", 
      "Escherichia", 
      "complex wiring", 
      "cells", 
      "different parts", 
      "level of networks", 
      "interaction", 
      "function", 
      "patterns", 
      "response", 
      "advances", 
      "basic computational elements", 
      "signals", 
      "levels", 
      "structure", 
      "network", 
      "analysis", 
      "elements", 
      "collection", 
      "amount", 
      "part", 
      "appearance", 
      "wiring", 
      "information", 
      "such networks", 
      "approach", 
      "frequency", 
      "program", 
      "view", 
      "notion", 
      "interconnection", 
      "computational elements", 
      "new algorithm", 
      "design", 
      "data collection", 
      "algorithm", 
      "basic building blocks2", 
      "building blocks2", 
      "blocks2", 
      "temporal expression programs"
    ], 
    "name": "Network motifs in the transcriptional regulation network of Escherichia coli", 
    "pagination": "64-68", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1010954918"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/ng881"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "11967538"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/ng881", 
      "https://app.dimensions.ai/details/publication/pub.1010954918"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-01-01T18:12", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/article/article_358.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1038/ng881"
  }
]
 

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/pub.10.1038/ng881'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/ng881'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/ng881'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/ng881'


 

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

206 TRIPLES      22 PREDICATES      105 URIs      93 LITERALS      17 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/ng881 schema:about N00b3972f0b88462eb14232cb874987e3
2 N3b6963d682f84d3bad12ed03852e08f6
3 N4fe0c05015eb4433b5d0ef25a798fce5
4 N6d98d86fbdaa455a98616317f03bdbf1
5 N6db341c358404151b3d35533868d99f4
6 Na561a9cd375a45819976b6c4c3e1ade0
7 Na5a6f2495263446fa8850acb0f85e655
8 Nbf2d6b6251bc47cebb8ea31ca6e65ece
9 Nda84219f226b44329260197fc8603ee7
10 Ne4449be27832454ba62f34d51532b76e
11 anzsrc-for:06
12 anzsrc-for:0604
13 schema:author N0be6f977e8574239af59d23f2f4be264
14 schema:citation sg:pub.10.1038/35011540
15 sg:pub.10.1038/35036627
16 sg:pub.10.1038/35065725
17 sg:pub.10.1038/376307a0
18 schema:datePublished 2002-04-22
19 schema:datePublishedReg 2002-04-22
20 schema:description Little is known about the design principles1,2,3,4,5,6,7,8,9,10 of transcriptional regulation networks that control gene expression in cells. Recent advances in data collection and analysis2,11,12, however, are generating unprecedented amounts of information about gene regulation networks. To understand these complex wiring diagrams1,2,3,4,5,6,7,8,9,10,13, we sought to break down such networks into basic building blocks2. We generalize the notion of motifs, widely used for sequence analysis, to the level of networks. We define 'network motifs' as patterns of interconnections that recur in many different parts of a network at frequencies much higher than those found in randomized networks. We applied new algorithms for systematically detecting network motifs to one of the best-characterized regulation networks, that of direct transcriptional interactions in Escherichia coli3,6. We find that much of the network is composed of repeated appearances of three highly significant motifs. Each network motif has a specific function in determining gene expression, such as generating temporal expression programs and governing the responses to fluctuating external signals. The motif structure also allows an easily interpretable view of the entire known transcriptional network of the organism. This approach may help define the basic computational elements of other biological networks.
21 schema:genre article
22 schema:inLanguage en
23 schema:isAccessibleForFree true
24 schema:isPartOf N6c032fe52157475ca3849b5612f2f053
25 Nb85f38dda11f490c95af68bd9f283bbf
26 sg:journal.1103138
27 schema:keywords Escherichia
28 Escherichia coli
29 advances
30 algorithm
31 amount
32 analysis
33 appearance
34 approach
35 basic building blocks2
36 basic computational elements
37 biological networks
38 blocks2
39 building blocks2
40 cells
41 coli
42 collection
43 complex wiring
44 computational elements
45 data collection
46 design
47 different parts
48 direct transcriptional interactions
49 elements
50 expression
51 expression programs
52 external signals
53 frequency
54 function
55 gene expression
56 gene regulation networks
57 information
58 interaction
59 interconnection
60 interpretable view
61 level of networks
62 levels
63 motif
64 motif structure
65 network
66 network motifs
67 new algorithm
68 notion
69 notion of motif
70 organisms
71 part
72 pattern of interconnections
73 patterns
74 program
75 randomized networks
76 recent advances
77 regulation network
78 response
79 sequence analysis
80 signals
81 significant motifs
82 specific functions
83 structure
84 such networks
85 temporal expression programs
86 transcriptional interactions
87 transcriptional networks
88 transcriptional regulation network
89 unprecedented amount
90 view
91 wiring
92 schema:name Network motifs in the transcriptional regulation network of Escherichia coli
93 schema:pagination 64-68
94 schema:productId N9229f30699fe4e8a84bc505ac290e62a
95 N97cd04c895114e54b7df52a9a739fa40
96 Nd6bc78000cbc44d492b798c7773cff53
97 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010954918
98 https://doi.org/10.1038/ng881
99 schema:sdDatePublished 2022-01-01T18:12
100 schema:sdLicense https://scigraph.springernature.com/explorer/license/
101 schema:sdPublisher N80e82cf9d2304efa93048e2b95c8e6db
102 schema:url https://doi.org/10.1038/ng881
103 sgo:license sg:explorer/license/
104 sgo:sdDataset articles
105 rdf:type schema:ScholarlyArticle
106 N00b3972f0b88462eb14232cb874987e3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
107 schema:name Transcription Factors
108 rdf:type schema:DefinedTerm
109 N0be6f977e8574239af59d23f2f4be264 rdf:first sg:person.01213007720.49
110 rdf:rest N4b743eb7bffd4fe1918c7817cc5230f9
111 N1501544851ba458ea45da37bf495afa0 rdf:first sg:person.01310216122.13
112 rdf:rest rdf:nil
113 N3b6963d682f84d3bad12ed03852e08f6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
114 schema:name Signal Transduction
115 rdf:type schema:DefinedTerm
116 N4b743eb7bffd4fe1918c7817cc5230f9 rdf:first sg:person.0774352340.01
117 rdf:rest N4fa03a0684a249508017f6653e1949b2
118 N4fa03a0684a249508017f6653e1949b2 rdf:first sg:person.016437275623.42
119 rdf:rest N1501544851ba458ea45da37bf495afa0
120 N4fe0c05015eb4433b5d0ef25a798fce5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
121 schema:name Escherichia coli
122 rdf:type schema:DefinedTerm
123 N6c032fe52157475ca3849b5612f2f053 schema:volumeNumber 31
124 rdf:type schema:PublicationVolume
125 N6d98d86fbdaa455a98616317f03bdbf1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
126 schema:name Models, Genetic
127 rdf:type schema:DefinedTerm
128 N6db341c358404151b3d35533868d99f4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
129 schema:name Genes, Bacterial
130 rdf:type schema:DefinedTerm
131 N80e82cf9d2304efa93048e2b95c8e6db schema:name Springer Nature - SN SciGraph project
132 rdf:type schema:Organization
133 N9229f30699fe4e8a84bc505ac290e62a schema:name pubmed_id
134 schema:value 11967538
135 rdf:type schema:PropertyValue
136 N97cd04c895114e54b7df52a9a739fa40 schema:name dimensions_id
137 schema:value pub.1010954918
138 rdf:type schema:PropertyValue
139 Na561a9cd375a45819976b6c4c3e1ade0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
140 schema:name Transcription, Genetic
141 rdf:type schema:DefinedTerm
142 Na5a6f2495263446fa8850acb0f85e655 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
143 schema:name Databases, Genetic
144 rdf:type schema:DefinedTerm
145 Nb85f38dda11f490c95af68bd9f283bbf schema:issueNumber 1
146 rdf:type schema:PublicationIssue
147 Nbf2d6b6251bc47cebb8ea31ca6e65ece schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
148 schema:name Gene Expression Regulation, Bacterial
149 rdf:type schema:DefinedTerm
150 Nd6bc78000cbc44d492b798c7773cff53 schema:name doi
151 schema:value 10.1038/ng881
152 rdf:type schema:PropertyValue
153 Nda84219f226b44329260197fc8603ee7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
154 schema:name Regulon
155 rdf:type schema:DefinedTerm
156 Ne4449be27832454ba62f34d51532b76e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
157 schema:name Algorithms
158 rdf:type schema:DefinedTerm
159 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
160 schema:name Biological Sciences
161 rdf:type schema:DefinedTerm
162 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
163 schema:name Genetics
164 rdf:type schema:DefinedTerm
165 sg:journal.1103138 schema:issn 1061-4036
166 1546-1718
167 schema:name Nature Genetics
168 schema:publisher Springer Nature
169 rdf:type schema:Periodical
170 sg:person.01213007720.49 schema:affiliation grid-institutes:grid.13992.30
171 schema:familyName Shen-Orr
172 schema:givenName Shai S.
173 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213007720.49
174 rdf:type schema:Person
175 sg:person.01310216122.13 schema:affiliation grid-institutes:grid.13992.30
176 schema:familyName Alon
177 schema:givenName Uri
178 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01310216122.13
179 rdf:type schema:Person
180 sg:person.016437275623.42 schema:affiliation grid-institutes:grid.13992.30
181 schema:familyName Mangan
182 schema:givenName Shmoolik
183 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016437275623.42
184 rdf:type schema:Person
185 sg:person.0774352340.01 schema:affiliation grid-institutes:grid.13992.30
186 schema:familyName Milo
187 schema:givenName Ron
188 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0774352340.01
189 rdf:type schema:Person
190 sg:pub.10.1038/35011540 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019498862
191 https://doi.org/10.1038/35011540
192 rdf:type schema:CreativeWork
193 sg:pub.10.1038/35036627 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051510804
194 https://doi.org/10.1038/35036627
195 rdf:type schema:CreativeWork
196 sg:pub.10.1038/35065725 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005249327
197 https://doi.org/10.1038/35065725
198 rdf:type schema:CreativeWork
199 sg:pub.10.1038/376307a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044112594
200 https://doi.org/10.1038/376307a0
201 rdf:type schema:CreativeWork
202 grid-institutes:grid.13992.30 schema:alternateName Department of Molecular Cell Biology, Weizmann Institute of Science, 76100, Rehovot, Israel
203 Department of Physics of Complex Systems, Weizmann Institute of Science, 76100, Rehovot, Israel
204 schema:name Department of Molecular Cell Biology, Weizmann Institute of Science, 76100, Rehovot, Israel
205 Department of Physics of Complex Systems, Weizmann Institute of Science, 76100, Rehovot, Israel
206 rdf:type schema:Organization
 




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


...