title: Network-based analysis of genotype-phenotype correlations between different inheritance modes.
abstract: BACKGROUND
  Recent studies on human disease have revealed that aberrant interaction between proteins probably underlies a substantial number of human genetic diseases. This suggests a need to investigate disease inheritance mode using interaction, and based on which to refresh our conceptual understanding of a series of properties regarding inheritance mode of human disease.
  
  
  RESULTS
  We observed a strong correlation between the number of protein interactions and the likelihood of a gene causing any dominant diseases or multiple dominant diseases, whereas no correlation was observed between protein interaction and the likelihood of a gene causing recessive diseases. We found that dominant diseases are more likely to be associated with disruption of important interactions. These suggest inheritance mode should be understood using protein interaction. We therefore reviewed the previous studies and refined an interaction model of inheritance mode, and then confirmed that this model is largely reasonable using new evidences. With these findings, we found that the inheritance mode of human genetic diseases can be predicted using protein interaction. By integrating the systems biology perspectives with the classical disease genetics paradigm, our study provides some new insights into genotype-phenotype correlations.
  
  
  BACKGROUND
  haodapeng@ems.hrbmu.edu.cn or biofomeng@hotmail.com
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.
authors: Dapeng
authors: D
authors: Hao
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.
authors: Chuanxing
authors: C
authors: Li
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.
authors: Shaojun
authors: S
authors: Zhang
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.
authors: Jianping
authors: J
authors: Lu
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.
authors: Yongshuai
authors: Y
authors: Jiang
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.
authors: Shiyuan
authors: S
authors: Wang
authors: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, P.R. China and Institute for Systems Biology, Seattle 98109, USA.
authors: Meng
authors: M
authors: Zhou
mesh_terms: D004194:Disease / Q000235:genetics*; D056726:Genetic Association Studies / Q000379:methods*; D005838:Genotype; D006801:Humans; D040582:Inheritance Patterns; D009154:Mutation; D010641:Phenotype; D025941:Protein Interaction Mapping