2006
AUTHORSNikola Stojanovic , Piotr Berman
ABSTRACTThe study of variation in DNA sequences, within the framework of phylogeny or population genetics, for instance, is one of the most important subjects in modern genomics. We here present a new linear-time algorithm for finding maximal k-regions in alignments of three sequences, which can be used for the detection of segments featuring a certain degree of similarity, as well as the boundaries of distinct genomic environments such as gene clusters or haplotype blocks. k-regions are defined as these which have a center sequence whose Hamming distance from any of the alignment rows is at most k, and their determination in the general case is known to be NP-hard. More... »
PAGES344-354
Algorithms in Bioinformatics
ISBN
978-3-540-39583-6
978-3-540-39584-3
http://scigraph.springernature.com/pub.10.1007/11851561_32
DOIhttp://dx.doi.org/10.1007/11851561_32
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1028212990
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"
}
],
"author": [
{
"affiliation": {
"alternateName": "Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, Texas, USA",
"id": "http://www.grid.ac/institutes/grid.267315.4",
"name": [
"Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, Texas, USA"
],
"type": "Organization"
},
"familyName": "Stojanovic",
"givenName": "Nikola",
"id": "sg:person.01012555463.19",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01012555463.19"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Computer Science and Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA",
"id": "http://www.grid.ac/institutes/grid.29857.31",
"name": [
"Department of Computer Science and Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA"
],
"type": "Organization"
},
"familyName": "Berman",
"givenName": "Piotr",
"id": "sg:person.01274506210.27",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01274506210.27"
],
"type": "Person"
}
],
"datePublished": "2006",
"datePublishedReg": "2006-01-01",
"description": "The study of variation in DNA sequences, within the framework of phylogeny or population genetics, for instance, is one of the most important subjects in modern genomics. We here present a new linear-time algorithm for finding maximal k-regions in alignments of three sequences, which can be used for the detection of segments featuring a certain degree of similarity, as well as the boundaries of distinct genomic environments such as gene clusters or haplotype blocks. k-regions are defined as these which have a center sequence whose Hamming distance from any of the alignment rows is at most k, and their determination in the general case is known to be NP-hard.",
"editor": [
{
"familyName": "B\u00fccher",
"givenName": "Philipp",
"type": "Person"
},
{
"familyName": "Moret",
"givenName": "Bernard M. E.",
"type": "Person"
}
],
"genre": "chapter",
"id": "sg:pub.10.1007/11851561_32",
"isAccessibleForFree": false,
"isPartOf": {
"isbn": [
"978-3-540-39583-6",
"978-3-540-39584-3"
],
"name": "Algorithms in Bioinformatics",
"type": "Book"
},
"keywords": [
"genomic environment",
"gene cluster",
"population genetics",
"modern genomics",
"genetic variation",
"DNA sequences",
"haplotype blocks",
"center sequence",
"sequence",
"study of variation",
"phylogeny",
"genomics",
"genetics",
"variation",
"K region",
"similarity",
"clusters",
"alignment",
"segments",
"environment",
"certain degree",
"rows",
"study",
"distance",
"detection of segments",
"determination",
"degree",
"important subject",
"detection",
"block",
"instances",
"boundaries",
"linear time algorithm",
"NPs",
"framework",
"cases",
"new linear-time algorithm",
"Hamming distance",
"subjects",
"algorithm",
"general case"
],
"name": "A Linear-Time Algorithm for Studying Genetic Variation",
"pagination": "344-354",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1028212990"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/11851561_32"
]
}
],
"publisher": {
"name": "Springer Nature",
"type": "Organisation"
},
"sameAs": [
"https://doi.org/10.1007/11851561_32",
"https://app.dimensions.ai/details/publication/pub.1028212990"
],
"sdDataset": "chapters",
"sdDatePublished": "2022-08-04T17:20",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220804/entities/gbq_results/chapter/chapter_429.jsonl",
"type": "Chapter",
"url": "https://doi.org/10.1007/11851561_32"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
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.10.1007/11851561_32'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/11851561_32'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/11851561_32'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/11851561_32'
This table displays all metadata directly associated to this object as RDF triples.
115 TRIPLES
22 PREDICATES
66 URIs
59 LITERALS
7 BLANK NODES
Subject | Predicate | Object | |
---|---|---|---|
1 | sg:pub.10.1007/11851561_32 | schema:about | anzsrc-for:06 |
2 | ″ | ″ | anzsrc-for:0604 |
3 | ″ | schema:author | N1064889ca2c743f2b9b20a23e8443be8 |
4 | ″ | schema:datePublished | 2006 |
5 | ″ | schema:datePublishedReg | 2006-01-01 |
6 | ″ | schema:description | The study of variation in DNA sequences, within the framework of phylogeny or population genetics, for instance, is one of the most important subjects in modern genomics. We here present a new linear-time algorithm for finding maximal k-regions in alignments of three sequences, which can be used for the detection of segments featuring a certain degree of similarity, as well as the boundaries of distinct genomic environments such as gene clusters or haplotype blocks. k-regions are defined as these which have a center sequence whose Hamming distance from any of the alignment rows is at most k, and their determination in the general case is known to be NP-hard. |
7 | ″ | schema:editor | N65e57bc3221d4261a5eef4ee40716922 |
8 | ″ | schema:genre | chapter |
9 | ″ | schema:isAccessibleForFree | false |
10 | ″ | schema:isPartOf | N9c91766354a34f38a09d26923bbe4f35 |
11 | ″ | schema:keywords | DNA sequences |
12 | ″ | ″ | Hamming distance |
13 | ″ | ″ | K region |
14 | ″ | ″ | NPs |
15 | ″ | ″ | algorithm |
16 | ″ | ″ | alignment |
17 | ″ | ″ | block |
18 | ″ | ″ | boundaries |
19 | ″ | ″ | cases |
20 | ″ | ″ | center sequence |
21 | ″ | ″ | certain degree |
22 | ″ | ″ | clusters |
23 | ″ | ″ | degree |
24 | ″ | ″ | detection |
25 | ″ | ″ | detection of segments |
26 | ″ | ″ | determination |
27 | ″ | ″ | distance |
28 | ″ | ″ | environment |
29 | ″ | ″ | framework |
30 | ″ | ″ | gene cluster |
31 | ″ | ″ | general case |
32 | ″ | ″ | genetic variation |
33 | ″ | ″ | genetics |
34 | ″ | ″ | genomic environment |
35 | ″ | ″ | genomics |
36 | ″ | ″ | haplotype blocks |
37 | ″ | ″ | important subject |
38 | ″ | ″ | instances |
39 | ″ | ″ | linear time algorithm |
40 | ″ | ″ | modern genomics |
41 | ″ | ″ | new linear-time algorithm |
42 | ″ | ″ | phylogeny |
43 | ″ | ″ | population genetics |
44 | ″ | ″ | rows |
45 | ″ | ″ | segments |
46 | ″ | ″ | sequence |
47 | ″ | ″ | similarity |
48 | ″ | ″ | study |
49 | ″ | ″ | study of variation |
50 | ″ | ″ | subjects |
51 | ″ | ″ | variation |
52 | ″ | schema:name | A Linear-Time Algorithm for Studying Genetic Variation |
53 | ″ | schema:pagination | 344-354 |
54 | ″ | schema:productId | N326290cbd82b4916905ce6cefdc3d86b |
55 | ″ | ″ | N6afd3a9f7fef40d5b031466c4a2c10fe |
56 | ″ | schema:publisher | Ne15de0a1ebcd4370b27f5cdd1dbe89ca |
57 | ″ | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1028212990 |
58 | ″ | ″ | https://doi.org/10.1007/11851561_32 |
59 | ″ | schema:sdDatePublished | 2022-08-04T17:20 |
60 | ″ | schema:sdLicense | https://scigraph.springernature.com/explorer/license/ |
61 | ″ | schema:sdPublisher | N32ba4dd87d794bab9f4ee7278f8731a6 |
62 | ″ | schema:url | https://doi.org/10.1007/11851561_32 |
63 | ″ | sgo:license | sg:explorer/license/ |
64 | ″ | sgo:sdDataset | chapters |
65 | ″ | rdf:type | schema:Chapter |
66 | N1064889ca2c743f2b9b20a23e8443be8 | rdf:first | sg:person.01012555463.19 |
67 | ″ | rdf:rest | N29bd312ca1df497d8c1e5e1b7afbab49 |
68 | N29bd312ca1df497d8c1e5e1b7afbab49 | rdf:first | sg:person.01274506210.27 |
69 | ″ | rdf:rest | rdf:nil |
70 | N326290cbd82b4916905ce6cefdc3d86b | schema:name | dimensions_id |
71 | ″ | schema:value | pub.1028212990 |
72 | ″ | rdf:type | schema:PropertyValue |
73 | N32ba4dd87d794bab9f4ee7278f8731a6 | schema:name | Springer Nature - SN SciGraph project |
74 | ″ | rdf:type | schema:Organization |
75 | N6498ef317cd94e8287e43e898584b6aa | schema:familyName | Moret |
76 | ″ | schema:givenName | Bernard M. E. |
77 | ″ | rdf:type | schema:Person |
78 | N65e57bc3221d4261a5eef4ee40716922 | rdf:first | Nb6e0bba0cf544c99b89d27c900947069 |
79 | ″ | rdf:rest | Nf5c0d79cc2184603be69913e059922f2 |
80 | N6afd3a9f7fef40d5b031466c4a2c10fe | schema:name | doi |
81 | ″ | schema:value | 10.1007/11851561_32 |
82 | ″ | rdf:type | schema:PropertyValue |
83 | N9c91766354a34f38a09d26923bbe4f35 | schema:isbn | 978-3-540-39583-6 |
84 | ″ | ″ | 978-3-540-39584-3 |
85 | ″ | schema:name | Algorithms in Bioinformatics |
86 | ″ | rdf:type | schema:Book |
87 | Nb6e0bba0cf544c99b89d27c900947069 | schema:familyName | Bücher |
88 | ″ | schema:givenName | Philipp |
89 | ″ | rdf:type | schema:Person |
90 | Ne15de0a1ebcd4370b27f5cdd1dbe89ca | schema:name | Springer Nature |
91 | ″ | rdf:type | schema:Organisation |
92 | Nf5c0d79cc2184603be69913e059922f2 | rdf:first | N6498ef317cd94e8287e43e898584b6aa |
93 | ″ | rdf:rest | rdf:nil |
94 | anzsrc-for:06 | schema:inDefinedTermSet | anzsrc-for: |
95 | ″ | schema:name | Biological Sciences |
96 | ″ | rdf:type | schema:DefinedTerm |
97 | anzsrc-for:0604 | schema:inDefinedTermSet | anzsrc-for: |
98 | ″ | schema:name | Genetics |
99 | ″ | rdf:type | schema:DefinedTerm |
100 | sg:person.01012555463.19 | schema:affiliation | grid-institutes:grid.267315.4 |
101 | ″ | schema:familyName | Stojanovic |
102 | ″ | schema:givenName | Nikola |
103 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01012555463.19 |
104 | ″ | rdf:type | schema:Person |
105 | sg:person.01274506210.27 | schema:affiliation | grid-institutes:grid.29857.31 |
106 | ″ | schema:familyName | Berman |
107 | ″ | schema:givenName | Piotr |
108 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01274506210.27 |
109 | ″ | rdf:type | schema:Person |
110 | grid-institutes:grid.267315.4 | schema:alternateName | Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, Texas, USA |
111 | ″ | schema:name | Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, Texas, USA |
112 | ″ | rdf:type | schema:Organization |
113 | grid-institutes:grid.29857.31 | schema:alternateName | Department of Computer Science and Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA |
114 | ″ | schema:name | Department of Computer Science and Engineering, The Pennsylvania State University, University Park, Pennsylvania, USA |
115 | ″ | rdf:type | schema:Organization |