Ontology type: schema:Chapter
2017
AUTHORSE. V. Korotkov , M. A. Korotkova
ABSTRACTA mathematical method was developed in this study to determine tandem repeats in a DNA sequence. A multiple alignment of periods was calculated by direct optimization of the position-weight matrix (PWM) without using pairwise alignments or searching for similarity between periods. Random PWMs were used to develop a new mathematical algorithm for periodicity search. The developed algorithm was applied to analyze the DNA sequences of C. elegans genome. 25360 regions having a periodicity with length of 2 to 50 bases were found. On the average, a periodicity of ~4000 nucleotides was found to be associated with each region. A significant portion of the revealed regions have periods consisting of 10 and 11 nucleotides, multiple to 10 nucleotides and periods in the vicinity of 35 nucleotides. Only ~30% of the periods found were discovered early. This study discussed the origin of periodicity with insertions and deletions. More... »
PAGES445-456
Bioinformatics and Biomedical Engineering
ISBN
978-3-319-56153-0
978-3-319-56154-7
http://scigraph.springernature.com/pub.10.1007/978-3-319-56154-7_40
DOIhttp://dx.doi.org/10.1007/978-3-319-56154-7_40
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1084744998
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/2008/0102",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Applied Mathematics",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Mathematical Sciences",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Moscow Engineering Physics Institute",
"id": "https://www.grid.ac/institutes/grid.183446.c",
"name": [
"Institute of Bioengineering, Research Center of Biotechnology of the Russian Academy of Sciences",
"National Research Nuclear University \u201cMEPhI\u201d"
],
"type": "Organization"
},
"familyName": "Korotkov",
"givenName": "E. V.",
"id": "sg:person.01274151123.51",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01274151123.51"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Moscow Engineering Physics Institute",
"id": "https://www.grid.ac/institutes/grid.183446.c",
"name": [
"National Research Nuclear University \u201cMEPhI\u201d"
],
"type": "Organization"
},
"familyName": "Korotkova",
"givenName": "M. A.",
"id": "sg:person.01127050710.59",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01127050710.59"
],
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1016/j.jmb.2004.08.068",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1001122707"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3389/fbioe.2015.00031",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1006992834"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btg268",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1009106097"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/13.3.263",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011884358"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btq209",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014039743"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3329/agric.v13i1.26559",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1017417082"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3329/agric.v13i1.26559",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1017417082"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/15.3.187",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1018406111"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/dnares/dsl004",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019656483"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/bies.200800165",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020151872"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bib/bbs023",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020671143"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ygeno.2010.08.001",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020951977"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1128/mmbr.00011-08",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021073460"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btk032",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022495316"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/0022-2836(81)90087-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1024589839"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2105-6-206",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027800492",
"https://doi.org/10.1186/1471-2105-6-206"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.bbagrm.2008.07.002",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030667126"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btp482",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1031311066"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.compbiolchem.2014.08.008",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1033922445"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1145/974614.974644",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034864799"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1145/974614.974644",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034864799"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/27.2.573",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035372973"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1515/sagmb-2015-0079",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036424484"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkg617",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1037102854"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/nar/gkm360",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1037970477"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1093/bioinformatics/btm097",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1041329179"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0960-9822(02)01220-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1051011805"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0960-9822(02)01220-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1051011805"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s0960-9822(02)01220-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1051011805"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1023/a:1024231109360",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1052064279",
"https://doi.org/10.1023/a:1024231109360"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1089/cmb.2006.13.946",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1059245516"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3367/ufnr.0170.200001c.0057",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1071219535"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.6026/97320630005221",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1073594141"
],
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1075303427",
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1077259371",
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1017/cbo9780511790492",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1098676015"
],
"type": "CreativeWork"
}
],
"datePublished": "2017",
"datePublishedReg": "2017-01-01",
"description": "A mathematical method was developed in this study to determine tandem repeats in a DNA sequence. A multiple alignment of periods was calculated by direct optimization of the position-weight matrix (PWM) without using pairwise alignments or searching for similarity between periods. Random PWMs were used to develop a new mathematical algorithm for periodicity search. The developed algorithm was applied to analyze the DNA sequences of C. elegans genome. 25360 regions having a periodicity with length of 2 to 50 bases were found. On the average, a periodicity of ~4000 nucleotides was found to be associated with each region. A significant portion of the revealed regions have periods consisting of 10 and 11 nucleotides, multiple to 10 nucleotides and periods in the vicinity of 35 nucleotides. Only ~30% of the periods found were discovered early. This study discussed the origin of periodicity with insertions and deletions.",
"editor": [
{
"familyName": "Rojas",
"givenName": "Ignacio",
"type": "Person"
},
{
"familyName": "Ortu\u00f1o",
"givenName": "Francisco",
"type": "Person"
}
],
"genre": "chapter",
"id": "sg:pub.10.1007/978-3-319-56154-7_40",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": {
"isbn": [
"978-3-319-56153-0",
"978-3-319-56154-7"
],
"name": "Bioinformatics and Biomedical Engineering",
"type": "Book"
},
"name": "Search of Regions with Periodicity Using Random Position Weight Matrices in the Genome of C. elegans",
"pagination": "445-456",
"productId": [
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/978-3-319-56154-7_40"
]
},
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"2d4592206500a951cc98d41d1ed11c3e8d2babaa428eadc928398cdcc02702c5"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1084744998"
]
}
],
"publisher": {
"location": "Cham",
"name": "Springer International Publishing",
"type": "Organisation"
},
"sameAs": [
"https://doi.org/10.1007/978-3-319-56154-7_40",
"https://app.dimensions.ai/details/publication/pub.1084744998"
],
"sdDataset": "chapters",
"sdDatePublished": "2019-04-15T18:51",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8681_00000600.jsonl",
"type": "Chapter",
"url": "http://link.springer.com/10.1007/978-3-319-56154-7_40"
}
]
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.10.1007/978-3-319-56154-7_40'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-56154-7_40'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-56154-7_40'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-56154-7_40'
This table displays all metadata directly associated to this object as RDF triples.
174 TRIPLES
23 PREDICATES
59 URIs
20 LITERALS
8 BLANK NODES