Similarity computation strategies in the microRNA-disease network: a survey

Various microRNAs have been demonstrated to play roles in a number of human diseases. Several microRNA-disease network reconstruction methods have been used to describe the association from a systems biology perspective. The key problem for the network is the similarity computation model. In this ar...

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Bibliographic Details
Published inBriefings in functional genomics Vol. 15; no. 1; pp. elv024 - 64
Main Authors Zou, Quan, Li, Jinjin, Song, Li, Zeng, Xiangxiang, Wang, Guohua
Format Journal Article
LanguageEnglish
Published England 01.01.2016
Subjects
Algorithms
bioinformatics
Computational Biology - methods
Disease - genetics
human diseases
Humans
Metabolic Networks and Pathways - genetics
microRNA
MicroRNAs - genetics
Phenotype
surveys
Surveys and Questionnaires
Systems Biology
microRNA
machine learning
microRNA–disease relationship
network
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Summary:Various microRNAs have been demonstrated to play roles in a number of human diseases. Several microRNA-disease network reconstruction methods have been used to describe the association from a systems biology perspective. The key problem for the network is the similarity computation model. In this article, we reviewed the main similarity computation methods and discussed these methods and future works. This survey may prompt and guide systems biology and bioinformatics researchers to build more perfect microRNA-disease associations and may make the network relationship clear for medical researchers.
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ISSN:2041-2649
2041-2657
2041-2657
DOI:10.1093/bfgp/elv024