About: Individual sequences in large sets of gene sequences may be distinguished efficiently by combinations of shared sub-sequences

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About: Individual sequences in large sets of gene sequences may be distinguished efficiently by combinations of shared sub-sequences Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Individual sequences in large sets of gene sequences may be distinguished efficiently by combinations of shared sub-sequences
Creator	Armstrong, John Gibbs, Adrian Gibbs, Mark
topic	covid:e6184d2db86268ba31e49b03a5aab475d5ce5ca6#this
Source	Medline; PMC
abstract	BACKGROUND: Most current DNA diagnostic tests for identifying organisms use specific oligonucleotide probes that are complementary in sequence to, and hence only hybridise with the DNA of one target species. By contrast, in traditional taxonomy, specimens are usually identified by 'dichotomous keys' that use combinations of characters shared by different members of the target set. Using one specific character for each target is the least efficient strategy for identification. Using combinations of shared bisectionally-distributed characters is much more efficient, and this strategy is most efficient when they separate the targets in a progressively binary way. RESULTS: We have developed a practical method for finding minimal sets of sub-sequences that identify individual sequences, and could be targeted by combinations of probes, so that the efficient strategy of traditional taxonomic identification could be used in DNA diagnosis. The sizes of minimal sub-sequence sets depended mostly on sequence diversity and sub-sequence length and interactions between these parameters. We found that 201 distinct cytochrome oxidase subunit-1 (CO1) genes from moths (Lepidoptera) were distinguished using only 15 sub-sequences 20 nucleotides long, whereas only 8–10 sub-sequences 6–10 nucleotides long were required to distinguish the CO1 genes of 92 species from the 9 largest orders of insects. CONCLUSION: The presence/absence of sub-sequences in a set of gene sequences can be used like the questions in a traditional dichotomous taxonomic key; hybridisation probes complementary to such sub-sequences should provide a very efficient means for identifying individual species, subtypes or genotypes. Sequence diversity and sub-sequence length are the major factors that determine the numbers of distinguishing sub-sequences in any set of sequences.
has issue date	2005-04-08(xsd:dateTime)
bibo:doi	10.1186/1471-2105-6-90
bibo:pmid	15817134
has license	cc-by
sha1sum (hex)	e6184d2db86268ba31e49b03a5aab475d5ce5ca6
schema:url	https://doi.org/10.1186/1471-2105-6-90
resource representing a document's title	Individual sequences in large sets of gene sequences may be distinguished efficiently by combinations of shared sub-sequences
has PubMed Central identifier	PMC1090557
has PubMed identifier	15817134
schema:publication	BMC Bioinformatics
resource representing a document's body	covid:e6184d2db86268ba31e49b03a5aab475d5ce5ca6#body_text
is http://vocab.deri.ie/void#inDataset of	https://covidontheweb.inria.fr:4443/about/id/http/ns.inria.fr/covid19/e6184d2db86268ba31e49b03a5aab475d5ce5ca6
is schema:about of	named entity 'diagnostic tests' named entity 'organisms' named entity 'specific' named entity 'SUB-' named entity 'CHARACTER' named entity 'CHARACTERS' named entity 'USUALLY' named entity 'SEPARATE' named entity 'WAY' named entity 'MEMBERS' named entity 'SPECIES' named entity 'CURRENT' named entity 'OLIGONUCLEOTIDE PROBES' named entity 'TARGETS' named entity 'DNA' named entity 'BINARY' named entity 'INDIVIDUAL' named entity 'LARGE' named entity 'CONTRAST' named entity 'TAXONOMY' named entity 'SEQUENCE' named entity 'TARGET' named entity 'STRATEGY' named entity 'DISTRIBUTED' named entity 'USING' named entity 'SHARED' named entity 'MAY BE' named entity 'BACKGROUND' named entity 'SPECIFIC' named entity 'SHARED' named entity 'SET' named entity 'MUCH' named entity 'EFFICIENT' named entity 'IDENTIFICATION' named entity 'KEYS' named entity 'DIAGNOSTIC TESTS' named entity 'DIFFERENT' named entity 'USE' named entity 'GENE' named entity 'SEQUENCES' named entity 'COMBINATIONS' named entity 'IDENTIFIED BY' named entity 'COMBINATIONS' named entity 'ORGANISMS' named entity 'SPECIMENS' named entity 'TRADITIONAL' named entity 'IDENTIFYING' covid:arg/e6184d2db86268ba31e49b03a5aab475d5ce5ca6 named entity 'target' named entity 'identification' named entity 'species' named entity 'DNA' named entity 'hybridise' named entity 'target set' named entity 'species' named entity 'gene sequences' named entity 'CO1' named entity 'taxonomic key' named entity 'CO1' named entity 'phylogenetic' named entity 'double-stranded' named entity 'CO1' named entity 'CO1' named entity 'DSSs' named entity 'bioinformatically' named entity 'RNA' named entity 'oligonucleotide probes' named entity 'medical diagnostics' named entity 'bioinformatic' named entity 'viruses' named entity 'plant viruses' named entity 'bacteria' named entity 'pathogens' named entity 'DSSs' named entity 'data-sets' named entity 'nucleotide' named entity 'DSSs'

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