University Library
  • Login
A gateway to Melbourne's research publications
Minerva Access is the University's Institutional Repository. It aims to collect, preserve, and showcase the intellectual output of staff and students of the University of Melbourne for a global audience.
View Item 
  • Minerva Access
  • Medicine, Dentistry & Health Sciences
  • Melbourne Medical School
  • Clinical Pathology
  • Clinical Pathology - Research Publications
  • View Item
  • Minerva Access
  • Medicine, Dentistry & Health Sciences
  • Melbourne Medical School
  • Clinical Pathology
  • Clinical Pathology - Research Publications
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

    Computational selection and prioritization of candidate genes for Fetal Alcohol Syndrome

    Thumbnail
    Download
    Published version (462.8Kb)

    Citations
    Scopus
    Web of Science
    Altmetric
    29
    28
    Author
    Lombard, Z; Tiffin, N; Hofmann, O; Bajic, VB; Hide, W; Ramsay, M
    Date
    2007-10-25
    Source Title
    BMC Genomics
    Publisher
    BMC
    University of Melbourne Author/s
    Hofmann, Oliver
    Affiliation
    Clinical Pathology
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Lombard, Z., Tiffin, N., Hofmann, O., Bajic, V. B., Hide, W. & Ramsay, M. (2007). Computational selection and prioritization of candidate genes for Fetal Alcohol Syndrome. BMC GENOMICS, 8 (1), https://doi.org/10.1186/1471-2164-8-389.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/254681
    DOI
    10.1186/1471-2164-8-389
    Abstract
    BACKGROUND: Fetal alcohol syndrome (FAS) is a serious global health problem and is observed at high frequencies in certain South African communities. Although in utero alcohol exposure is the primary trigger, there is evidence for genetic- and other susceptibility factors in FAS development. No genome-wide association or linkage studies have been performed for FAS, making computational selection and -prioritization of candidate disease genes an attractive approach. RESULTS: 10174 Candidate genes were initially selected from the whole genome using a previously described method, which selects candidate genes according to their expression in disease-affected tissues. Hereafter candidates were prioritized for experimental investigation by investigating criteria pertinent to FAS and binary filtering. 29 Criteria were assessed by mining various database sources to populate criteria-specific gene lists. Candidate genes were then prioritized for experimental investigation using a binary system that assessed the criteria gene lists against the candidate list, and candidate genes were scored accordingly. A group of 87 genes was prioritized as candidates and for future experimental validation. The validity of the binary prioritization method was assessed by investigating the protein-protein interactions, functional enrichment and common promoter element binding sites of the top-ranked genes. CONCLUSION: This analysis highlighted a list of strong candidate genes from the TGF-beta, MAPK and Hedgehog signalling pathways, which are all integral to fetal development and potential targets for alcohol's teratogenic effect. We conclude that this novel bioinformatics approach effectively prioritizes credible candidate genes for further experimental analysis.

    Export Reference in RIS Format     

    Endnote

    • Click on "Export Reference in RIS Format" and choose "open with... Endnote".

    Refworks

    • Click on "Export Reference in RIS Format". Login to Refworks, go to References => Import References


    Collections
    • Minerva Elements Records [53102]
    • Clinical Pathology - Research Publications [620]
    Minerva AccessDepositing Your Work (for University of Melbourne Staff and Students)NewsFAQs

    BrowseCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects
    My AccountLoginRegister
    StatisticsMost Popular ItemsStatistics by CountryMost Popular Authors