Literature DB >> 24665902

Computational disease gene prioritization: an appraisal.

Nivit Gill1, Shailendra Singh, Trilok C Aseri.   

Abstract

Bioinformatics aids in the understanding of the biological processes of living beings and the genetic architecture of human diseases. The discovery of disease-related genes improves the diagnosis and therapy design for the disease. To save the cost and time involved in the experimental verification of the candidate genes, computational methods are employed for ranking the genes according to their likelihood of being associated with the disease. Only top-ranked genes are then verified experimentally. A variety of methods have been conceived by the researchers for the prioritization of the disease candidate genes, which differ in the data source being used or the scoring function used for ranking the genes. A review of various aspects of computational disease gene prioritization and its research issues is presented in this article. The aspects covered are gene prioritization process, data sources used, types of prioritization methods, and performance assessment methods. This article provides a brief overview and acts as a quick guide for disease gene prioritization.

Entities:  

Keywords:  candidate gene prioritization; disease gene; gene ranking; network analysis method; similarity profiling method; text mining method

Mesh:

Year:  2014        PMID: 24665902     DOI: 10.1089/cmb.2013.0158

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  15 in total

1.  Lengths of Orthologous Prokaryotic Proteins Are Affected by Evolutionary Factors.

Authors:  Tatiana Tatarinova; Bilal Salih; Jennifer Dien Bard; Irit Cohen; Alexander Bolshoy
Journal:  Biomed Res Int       Date:  2015-05-31       Impact factor: 3.411

2.  Identification of Essential Proteins Based on a New Combination of Local Interaction Density and Protein Complexes.

Authors:  Jiawei Luo; Yi Qi
Journal:  PLoS One       Date:  2015-06-30       Impact factor: 3.240

3.  FLAGS, frequently mutated genes in public exomes.

Authors:  Casper Shyr; Maja Tarailo-Graovac; Michael Gottlieb; Jessica J Y Lee; Clara van Karnebeek; Wyeth W Wasserman
Journal:  BMC Med Genomics       Date:  2014-12-03       Impact factor: 3.063

4.  Constructing an integrated gene similarity network for the identification of disease genes.

Authors:  Zhen Tian; Maozu Guo; Chunyu Wang; LinLin Xing; Lei Wang; Yin Zhang
Journal:  J Biomed Semantics       Date:  2017-09-20

5.  Arete - candidate gene prioritization using biological network topology with additional evidence types.

Authors:  Artem Lysenko; Keith Anthony Boroevich; Tatsuhiko Tsunoda
Journal:  BioData Min       Date:  2017-07-06       Impact factor: 2.522

6.  GenePANDA-a novel network-based gene prioritizing tool for complex diseases.

Authors:  Tianshu Yin; Shu Chen; Xiaohui Wu; Weidong Tian
Journal:  Sci Rep       Date:  2017-03-02       Impact factor: 4.379

7.  MGOGP: a gene module-based heuristic algorithm for cancer-related gene prioritization.

Authors:  Lingtao Su; Guixia Liu; Tian Bai; Xiangyu Meng; Qingshan Ma
Journal:  BMC Bioinformatics       Date:  2018-06-05       Impact factor: 3.169

8.  The development of precision medicine in clinical practice.

Authors:  Mingyan He; Jinglin Xia; Mohamed Shehab; Xiangdong Wang
Journal:  Clin Transl Med       Date:  2015-08-25

9.  SoftPanel: a website for grouping diseases and related disorders for generation of customized panels.

Authors:  Likun Wang; Cong Zhang; Johnathan Watkins; Yan Jin; Michael McNutt; Yuxin Yin
Journal:  BMC Bioinformatics       Date:  2016-04-05       Impact factor: 3.169

10.  Molecular mechanisms involved in the side effects of fatty acid amide hydrolase inhibitors: a structural phenomics approach to proteome-wide cellular off-target deconvolution and disease association.

Authors:  Shihab Dider; Jiadong Ji; Zheng Zhao; Lei Xie
Journal:  NPJ Syst Biol Appl       Date:  2016-11-10
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