A Bayesian analysis of the chromosome architecture of human disorders by integrating reductionist data

Frank Emmert-Streib, Ricardo De Matos Simoes, Shailesh Tripathi, Galina V. Glazko, Matthias Dehmer

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we present a Bayesian approach to estimate a chromosome and a disorder network from the Online Mendelian Inheritance in Man (OMIM) database. In contrast to other approaches, we obtain statistic rather than deterministic networks enabling a parametric control in the uncertainty of the underlying disorder-disease gene associations contained in the OMIM, on which the networks are based. From a structural investigation of the chromosome network, we identify three chromosome subgroups that reflect architectural differences in chromosome-disorder associations that are predictively exploitable for a functional analysis of diseases.

Original languageEnglish
Article number513
Pages (from-to)513
JournalScientific Reports
Volume2
DOIs
Publication statusPublished - 2012
Externally publishedYes

Keywords

  • Algorithms
  • Bayes Theorem
  • Chromosome Disorders/genetics
  • Computational Biology/methods
  • Databases, Genetic
  • Genetic Association Studies
  • Humans
  • Internet
  • Lod Score
  • Male
  • Models, Statistical
  • Molecular Sequence Annotation
  • Open Reading Frames
  • Physical Chromosome Mapping

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