Linked Life Data

10642879

Source:http://linkedlifedata.com/resource/pubmed/id/10642879

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2000-2-2
pubmed:abstractText
A new statistical model for DNA considers a sequence to be a mixture of regions with little structure and regions that are approximate repeats of other subsequences, i.e. instances of repeats do not need to match each other exactly. Both forward- and reverse-complementary repeats are allowed. The model has a small number of parameters which are fitted to the data. In general there are many explanations for a given sequence and how to compute the total probability of the data given the model is shown. Computer algorithms are described for these tasks. The model can be used to compute the information content of a sequence, either in total or base by base. This amounts to looking at sequences from a data-compression point of view and it is argued that this is a good way to tackle intelligent sequence analysis in general.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
0097-8485
pubmed:author
pubmed:issnType
Print
pubmed:volume
24
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
43-55
pubmed:dateRevised
2003-11-14
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Sequence complexity for biological sequence analysis.
pubmed:affiliation
School of Computer Science and Software Engineering, Monash University, Melbourne, Australia.
pubmed:publicationType
Journal Article