Literature DB >> 30854526

Mechanism-based disease similarity.

Mehdi B Hamaneh1, Yi-Kuo Yu1.   

Abstract

In recent years several methods have been proposed to assign pairwise mechanism- based similarity scores to human diseases. Despite their differences in approach and performance, these methods work in a somewhat similar manner: first a set of biomolecules (genes, proteins, chemicals, etc.) is associated with each disease, and then a measure is defined to calculate the similarity between the sets assigned to a pair of diseases. Since the similarity score between two diseases is defined based on the underlying molecular processes, a high score may hint at a shared cause, and therefore a similar treatment, for both diseases. This is of great practical importance especially when a rare or newly-discovered disease, for which limited information is available, is found to be related to a disease with a known treatment. Thus, in this mini-review we briefly discuss the recently developed methods for computing mechanism-based disease- disease similarities.

Entities:  

Keywords:  Disease-disease similarity; Disease-gene associations; Human disease network; Protein-protein interaction network; gene expression data; gene-gene association network

Year:  2016        PMID: 30854526      PMCID: PMC6404756          DOI: 10.29245/2572-9411/2016/3.1044

Source DB:  PubMed          Journal:  J Rare Dis Res Treat


  32 in total

1.  Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.

Authors:  M Ashburner; C A Ball; J A Blake; D Botstein; H Butler; J M Cherry; A P Davis; K Dolinski; S S Dwight; J T Eppig; M A Harris; D P Hill; L Issel-Tarver; A Kasarskis; S Lewis; J C Matese; J E Richardson; M Ringwald; G M Rubin; G Sherlock
Journal:  Nat Genet       Date:  2000-05       Impact factor: 38.330

2.  The genetic association database.

Authors:  Kevin G Becker; Kathleen C Barnes; Tiffani J Bright; S Alex Wang
Journal:  Nat Genet       Date:  2004-05       Impact factor: 38.330

3.  Global reconstruction of the human metabolic network based on genomic and bibliomic data.

Authors:  Natalie C Duarte; Scott A Becker; Neema Jamshidi; Ines Thiele; Monica L Mo; Thuy D Vo; Rohith Srivas; Bernhard Ø Palsson
Journal:  Proc Natl Acad Sci U S A       Date:  2007-01-31       Impact factor: 11.205

4.  The human disease network.

Authors:  Kwang-Il Goh; Michael E Cusick; David Valle; Barton Childs; Marc Vidal; Albert-László Barabási
Journal:  Proc Natl Acad Sci U S A       Date:  2007-05-14       Impact factor: 11.205

Review 5.  The implications of human metabolic network topology for disease comorbidity.

Authors:  D-S Lee; J Park; K A Kay; N A Christakis; Z N Oltvai; A-L Barabási
Journal:  Proc Natl Acad Sci U S A       Date:  2008-07-03       Impact factor: 11.205

6.  Human protein reference database as a discovery resource for proteomics.

Authors:  Suraj Peri; J Daniel Navarro; Troels Z Kristiansen; Ramars Amanchy; Vineeth Surendranath; Babylakshmi Muthusamy; T K B Gandhi; K N Chandrika; Nandan Deshpande; Shubha Suresh; B P Rashmi; K Shanker; N Padma; Vidya Niranjan; H C Harsha; Naveen Talreja; B M Vrushabendra; M A Ramya; A J Yatish; Mary Joy; H N Shivashankar; M P Kavitha; Minal Menezes; Dipanwita Roy Choudhury; Neelanjana Ghosh; R Saravana; Sreenath Chandran; Sujatha Mohan; Chandra Kiran Jonnalagadda; C K Prasad; Chandan Kumar-Sinha; Krishna S Deshpande; Akhilesh Pandey
Journal:  Nucleic Acids Res       Date:  2004-01-01       Impact factor: 16.971

7.  From genomics to chemical genomics: new developments in KEGG.

Authors:  Minoru Kanehisa; Susumu Goto; Masahiro Hattori; Kiyoko F Aoki-Kinoshita; Masumi Itoh; Shuichi Kawashima; Toshiaki Katayama; Michihiro Araki; Mika Hirakawa
Journal:  Nucleic Acids Res       Date:  2006-01-01       Impact factor: 16.971

8.  NCBI GEO: mining tens of millions of expression profiles--database and tools update.

Authors:  Tanya Barrett; Dennis B Troup; Stephen E Wilhite; Pierre Ledoux; Dmitry Rudnev; Carlos Evangelista; Irene F Kim; Alexandra Soboleva; Maxim Tomashevsky; Ron Edgar
Journal:  Nucleic Acids Res       Date:  2006-11-11       Impact factor: 16.971

9.  Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders.

Authors:  Ada Hamosh; Alan F Scott; Joanna S Amberger; Carol A Bocchini; Victor A McKusick
Journal:  Nucleic Acids Res       Date:  2005-01-01       Impact factor: 16.971

10.  A pathway-based view of human diseases and disease relationships.

Authors:  Yong Li; Pankaj Agarwal
Journal:  PLoS One       Date:  2009-02-04       Impact factor: 3.240

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