Linked Life Data

15303288

Source:http://linkedlifedata.com/resource/pubmed/id/15303288

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2004-8-10
pubmed:abstractText
There is a pressing need to align the growing set of expressed sequence tags (ESTs) with the newly sequenced human genome. However, the problem is complicated by the exon/intron structure of eukaryotic genes misread nucleotides in ESTs, and the millions of repetitive sequences in genomic sequences. To solve this problem, algorithms that use dynamic programming have been proposed. In reality, however, these algorithms require an enormous amount of processing time. In an effort to improve the computational efficiency of these classical DP algorithms, we developed software that fully utilizes lookup-tables to detect the start- and endpoints of an EST within a given DNA sequence efficiently, and subsequently promptly identify exons and introns. In addition, the locations of all splice sites must be calculated correctly with high sensitivity and accuracy, while retaining high computational efficiency. This goal is hard to accomplish in practice, due to misread nucleotides in ESTs and repetitive sequences in the genome. Nevertheless, we present two heuristics that effectively settle this issue. Experimental results confirm that our technique improves the overall computation time by orders of magnitude compared with common tools, such as SIM4 and BLAT, and simultaneously attains high sensitivity and accuracy against a clean dataset of documented genes.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
0219-7200
pubmed:author
pubmed:issnType
Print
pubmed:volume
1
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
363-86
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
A fast and sensitive algorithm for aligning ESTs to the human genome.
pubmed:affiliation
Department of Computational Biology, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-Shi, Chiba 277-8562, Japan. jun@gi.k.u-tokyo.ac.jp
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't, Evaluation Studies, Validation Studies