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Number of citations per year for the bioinformatics software tool MEMCover
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This map represents all the scientific publications referring to MEMCover per scientific context
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MEMCover specifications

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Unique identifier OMICS_22380
Name MEMCover
Alternative name Mutual Exclusivity Module Cover

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This tool is not maintained anymore.

Publication for Mutual Exclusivity Module Cover

MEMCover citations

 (6)
library_books

Graph theoretical comparison of normal and tumor networks in identifying BRCA genes

2017
BMC Syst Biol
PMCID: 5700672
PMID: 29166896
DOI: 10.1186/s12918-017-0495-0

[…] walk on the PPI network distributing the mutation frequencies of genes throughout the network, giving rise to a directed graph where the strongly connected components represent the output modules []. MEMCover combines mutual exclusivity data of mutations across several tissue types with the PPI network data to produce modules of cancer genes []. Although potentially useful for pan-cancer analysis, […]

library_books

Integrating omics data and protein interaction networks to prioritize driver genes in cancer

2017
Oncotarget
PMCID: 5601632
PMID: 28938536
DOI: 10.18632/oncotarget.19481

[…] xpression []. MUFFINN prioritizes driver genes based on genes and their neighbors in functional network []. In addition, some approaches were developed to identify driver modules or pathways, such as MEMCover and MEMo [, ]. Although these approaches are effective in detecting drivers, they have limitations. First, the network is built based on static network, rather being condition specific. Secon […]

library_books

Computational Methods for Characterizing Cancer Mutational Heterogeneity

2017
Front Genet
PMCID: 5469877
PMID: 28659971
DOI: 10.3389/fgene.2017.00083

[…] MEMo therefore identifies modules summarize inter-patient heterogeneity through mutual exclusivity, but it is unlikely to include in its modules genes that are not significantly mutated on their own. MEMCover (Kim et al., ) is a different algorithm that combines network information and mutual exclusivity of mutations to identify modules of mutated genes. MEMCover employs a greedy strategy to ident […]

library_books

Identification of driver modules in pan cancer via coordinating coverage and exclusivity

2017
Oncotarget
PMCID: 5482642
PMID: 28415609
DOI: 10.18632/oncotarget.16433

[…] was proposed for global module detection in complex networks []. HotNet2 [] is a network based method that delves into the long tail of rarely mutated genes and finds mutated subnetworks. MEMo [] and MEMCover [] are both network based methods to systematically identify mutually exclusive network modules. MEMo outputs the significantly exclusive modules evaluated by a random permutation testing met […]

library_books

Discovery of cancer common and specific driver gene sets

2017
Nucleic Acids Res
PMCID: 5449640
PMID: 28168295
DOI: 10.1093/nar/gkx089

[…] pan-cancer network analysis; Kim et al. () investigated different kinds of mutual exclusivity among multiple cancer types and designed statistical testing methods for driver gene set identification (MEMCover). Although recent pan-cancer studies revealed that some pairs of genes showing mutually exclusivity are common or specific for some cancer types (,), there is still a lack of systematic inves […]

library_books

Computational approaches for the identification of cancer genes and pathways

2016
Wiley Interdiscip Rev Syst Biol Med
PMCID: 5215607
PMID: 27863091
DOI: 10.1002/wsbm.1364

[…] compared to Dendrix, Multi‐Dendrix, MEMo, and RME.A unique approach for detecting mutually exclusive patterns of genetic alterations either within the same tissue or across different tissue types is MEMCover. MEMCover uses a random permutation test (similar to MEMo) systematically to detect mutually exclusive patterns that occur in one tissue type, in many tissue types, or between tissue‐specific […]


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MEMCover institution(s)
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
MEMCover funding source(s)
Supported by the Intramural Research Program of the National Institutes of Health, National Library of Medicine.

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