Managing Evidence from Multiple Gene Finding Resources via an XML-based Integration Architecture

While biological processes underlying gene expression are still under experimental research, computational gene prediction techniques have reached high level of sophistication with the employment of efficient intrinsic and extrinsic methods that identify protein-coding regions within query genomic s...

Full description

Bibliographic Details
Main Authors: Malousi Andigoni, Koutkias Vassilis, Maglaveras Nicos
Format: Article
Language:English
Published: De Gruyter 2005-12-01
Series:Journal of Integrative Bioinformatics
Online Access:https://doi.org/10.1515/jib-2005-16
id doaj-c5ea20b8d2a945e5ba9e82c0126d7504
record_format Article
spelling doaj-c5ea20b8d2a945e5ba9e82c0126d75042021-09-06T19:40:30ZengDe GruyterJournal of Integrative Bioinformatics1613-45162005-12-0121748310.1515/jib-2005-16biecoll-jib-2005-16Managing Evidence from Multiple Gene Finding Resources via an XML-based Integration ArchitectureMalousi Andigoni0Koutkias Vassilis1Maglaveras Nicos2Lab. of Medical Informatics, Faculty of Medicine, PO BOX 323, 54124, Aristotle University of Thessaloniki, GreeceLab. of Medical Informatics, Faculty of Medicine, PO BOX 323, 54124, Aristotle University of Thessaloniki, GreeceLab. of Medical Informatics, Faculty of Medicine, PO BOX 323, 54124, Aristotle University of Thessaloniki, GreeceWhile biological processes underlying gene expression are still under experimental research, computational gene prediction techniques have reached high level of sophistication with the employment of efficient intrinsic and extrinsic methods that identify protein-coding regions within query genomic sequences. Their ability though to delineate the exact exon boundaries is characterized by a trade off between sensitivity and specificity and still is prone to alternations in gene regulation during transcription and splicing and to inherent complexities introduced by the implemented methodology. Evaluation studies have shown that combinatorial approaches exhibit improved accuracy levels through the integration of evidence data from multiple resources that are further assessed in order to end up with the most probable gene assembly.https://doi.org/10.1515/jib-2005-16
collection DOAJ
language English
format Article
sources DOAJ
author Malousi Andigoni
Koutkias Vassilis
Maglaveras Nicos
spellingShingle Malousi Andigoni
Koutkias Vassilis
Maglaveras Nicos
Managing Evidence from Multiple Gene Finding Resources via an XML-based Integration Architecture
Journal of Integrative Bioinformatics
author_facet Malousi Andigoni
Koutkias Vassilis
Maglaveras Nicos
author_sort Malousi Andigoni
title Managing Evidence from Multiple Gene Finding Resources via an XML-based Integration Architecture
title_short Managing Evidence from Multiple Gene Finding Resources via an XML-based Integration Architecture
title_full Managing Evidence from Multiple Gene Finding Resources via an XML-based Integration Architecture
title_fullStr Managing Evidence from Multiple Gene Finding Resources via an XML-based Integration Architecture
title_full_unstemmed Managing Evidence from Multiple Gene Finding Resources via an XML-based Integration Architecture
title_sort managing evidence from multiple gene finding resources via an xml-based integration architecture
publisher De Gruyter
series Journal of Integrative Bioinformatics
issn 1613-4516
publishDate 2005-12-01
description While biological processes underlying gene expression are still under experimental research, computational gene prediction techniques have reached high level of sophistication with the employment of efficient intrinsic and extrinsic methods that identify protein-coding regions within query genomic sequences. Their ability though to delineate the exact exon boundaries is characterized by a trade off between sensitivity and specificity and still is prone to alternations in gene regulation during transcription and splicing and to inherent complexities introduced by the implemented methodology. Evaluation studies have shown that combinatorial approaches exhibit improved accuracy levels through the integration of evidence data from multiple resources that are further assessed in order to end up with the most probable gene assembly.
url https://doi.org/10.1515/jib-2005-16
work_keys_str_mv AT malousiandigoni managingevidencefrommultiplegenefindingresourcesviaanxmlbasedintegrationarchitecture
AT koutkiasvassilis managingevidencefrommultiplegenefindingresourcesviaanxmlbasedintegrationarchitecture
AT maglaverasnicos managingevidencefrommultiplegenefindingresourcesviaanxmlbasedintegrationarchitecture
_version_ 1717768409034260480