Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
1996-8-12
pubmed:abstractText
Automated and nonautomated approaches to chromosome classification involves assessing several chromosome attributes. The centromere is an important attribute which provides insight to other features such as chromosome orientation and the banding pattern sequence. Improving the ability to identify the centromere will enhance feature determination and analysis. Techniques to identify the centromere attempt to isolate specific centromere attributes. The centromere can be characterized as possessing the following properties: 1) usually the narrowest region in the chromosome image, 2) usually located in a region containing extreme concavities along the chromosome contour, and 3) usually located in a region of uniform dark grey-level. A centromere attribute integration approach for automated centromere identification has been developed which has a correct identification rate of 93.5% on a diversified data set. This approach determines and evaluates centromere candidates based on quantified centromere attributes. Centromere attribute integration incorporates other commonly used techniques for centromere identification. Some of the techniques integrated into the experimental algorithm include evaluating chromosome curvature, analyzing the shape profile, and inspecting the width profile.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0067-8856
pubmed:author
pubmed:issnType
Print
pubmed:volume
32
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
23-9
pubmed:dateRevised
2009-11-11
pubmed:meshHeading
pubmed:year
1996
pubmed:articleTitle
A centromere attribute integration approach to centromere identification.
pubmed:affiliation
University of Missouri Medical Informatics Group, Columbia 65211, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't