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MISIM specifications

Information


Unique identifier OMICS_11974
Name MISIM
Alternative name miRNA similarity
Interface Web user interface
Restrictions to use None
Computer skills Basic
Stability No
Maintained No

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Publications for miRNA similarity

MISIM citations

 (31)
library_books

Global Similarity Method Based on a Two tier Random Walk for the Prediction of microRNA–Disease Association

2018
Sci Rep
PMCID: 5915491
PMID: 29691434
DOI: 10.1038/s41598-018-24532-7

[…] NA information associated with a similar disease is introduced to optimise the initial associated miRNA of di.After the initial vector is obtained, the restarted random walk can be carried out in the miRNA similarity network to obtain a stable information distribution vector. The random walk formula is expressed as Eq. ().6D˜t+1=(1−γ)SIM¯D˜t+γD˜iwhere SIM¯ refers to the column normalization matrix […]

library_books

Prediction of microRNA disease associations based on distance correlation set

2018
BMC Bioinformatics
PMCID: 5905221
PMID: 29665774
DOI: 10.1186/s12859-018-2146-x

[…] of DCSMDA was not very satisfactory compared with that of several existing methods, such as LRSMDA and WBSMDA [, ]. Introducing more reliable measures for the calculations of the disease similarity, miRNA similarity, and lncRNA similarity and developing a more reliable similarity integration method could improve the performance of DCSMDA. Finally, DCSMDA cannot be applied to unknown diseases or m […]

library_books

Identifying diseases related metabolites using random walk

2018
BMC Bioinformatics
PMCID: 5907145
PMID: 29671398
DOI: 10.1186/s12859-018-2098-1

[…] A method named ‘MISIM’ was proposed by Dong Wang et al. [] which is used to estimate the similarity of micro-RNAs. In the research, they pointed out that the genes which have similar functions are often associated wi […]

call_split

SRMDAP: SimRank and Density Based Clustering Recommender Model for miRNA Disease Association Prediction

2018
Biomed Res Int
PMCID: 5884242
PMID: 29750163
DOI: 10.1155/2018/5747489
call_split See protocol

[…] Three datasets were used in our approach. Experimentally verified miRNA-mRNA interactions were downloaded from the miRTarBase database to construct the miRNA similarity network [] (http://mirtarbase.mbc.nctu.edu.tw/, Release 6.0: Sept-15-2015). Meanwhile, experimentally verified disease-related mRNAs were downloaded from the DisGeNET database [] (htt […]

library_books

NDAMDA: Network distance analysis for MiRNA‐disease association prediction

2018
J Cell Mol Med
PMCID: 5908143
PMID: 29532987
DOI: 10.1111/jcmm.13583

[…] ther iterative model named HGIMDA to find the optimal solutions based on global network similarity information. A heterogeneous graph was constructed from various disease similarity measures, diverse miRNA similarity measures and the known miRNA‐disease associations. To calculate the association score between a miRNA and a disease, an iterative process was carried out on the heterogeneous graph, s […]

library_books

A Semi Supervised Learning Algorithm for Predicting Four Types MiRNA Disease Associations by Mutual Information in a Heterogeneous Network

2018
Genes
PMCID: 5867860
PMID: 29498680
DOI: 10.3390/genes9030139

[…] at miRNAs with similar functions tend to be associated with similar diseases and vice versa [,]. Based on this assumption, Wang et al. [] provided a method to infer human miRNA functional similarity (MISIM) by measuring semantic similarity of diseases which associated with miRNAs. Furthermore, they constructed a miRNA functional network. On the basis of results studied in [], Xuan et al. [] calcul […]

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MISIM institution(s)
Department of Biomedical Informatics, Peking University Health Science Center, Beijing, China; MOE Key Laboratory of Molecular Cardiology, Peking University, Beijing, China; Science Department, Northwest A & F University, Shaanxi Key Lab Mol Biol Agr, Yangling, Shaanxi, China
MISIM funding source(s)
Natural Science Foundation of China (Grant no. 30900829)

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