Linked Life Data

20887262

Source:http://linkedlifedata.com/resource/pubmed/id/20887262

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
7
pubmed:dateCreated
2011-1-18
pubmed:abstractText
SBASE is a project initiated to detect known domain types and predicting domain architectures using sequence similarity searching (Simon et al., Protein Seq Data Anal, 5: 39-42, 1992, Pongor et al, Nucl. Acids. Res. 21:3111-3115, 1992). The current approach uses a curated collection of domain sequences - the SBASE domain library - and standard similarity search algorithms, followed by postprocessing which is based on a simple statistics of the domain similarity network (http://hydra.icgeb.trieste.it/sbase/). It is especially useful in detecting rare, atypical examples of known domain types which are sometimes missed even by more sophisticated methodologies. This approach does not require multiple alignment or machine learning techniques, and can be a useful complement to other domain detection methodologies. This article gives an overview of the project history as well as of the concepts and principles developed within this the project.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1875-5550
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
11
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
538-49
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Detecting atypical examples of known domain types by sequence similarity searching: the SBASE domain library approach.
pubmed:affiliation
Protein Structure and Bioinformatics, ICGEB, Trieste, Italy.
pubmed:publicationType
Journal Article, Review