Walking the Interactome for Prioritization of Candidate Disease Genes
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TLDR
This work presents a method for prioritization of candidate genes by use of a global network distance measure, random walk analysis, for definition of similarities in protein-protein interaction networks, significantly outperforming previous methods based on local distance measures.Abstract:
The identification of genes associated with hereditary disorders has contributed to improving medical care and to a better understanding of gene functions, interactions, and pathways. However, there are well over 1500 Mendelian disorders whose molecular basis remains unknown. At present, methods such as linkage analysis can identify the chromosomal region in which unknown disease genes are located, but the regions could contain up to hundreds of candidate genes. In this work, we present a method for prioritization of candidate genes by use of a global network distance measure, random walk analysis, for definition of similarities in protein-protein interaction networks. We tested our method on 110 disease-gene families with a total of 783 genes and achieved an area under the ROC curve of up to 98% on simulated linkage intervals of 100 genes surrounding the disease gene, significantly outperforming previous methods based on local distance measures. Our results not only provide an improved tool for positional-cloning projects but also add weight to the assumption that phenotypically similar diseases are associated with disturbances of subnetworks within the larger protein interactome that extend beyond the disease proteins themselves.read more
Citations
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Network Medicine: A Network-Based Approach to Human Disease
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ToppGene Suite for gene list enrichment analysis and candidate gene prioritization
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STRING 8—a global view on proteins and their functional interactions in 630 organisms
Lars Juhl Jensen,Michael Kuhn,Manuel Stark,Samuel Chaffron,Christopher J. Creevey,Jean Muller,T. Doerks,Philippe Julien,Alexander Roth,Milan Simonovic,Peer Bork,Christian von Mering +11 more
TL;DR: The most important new developments in STRING 8 over previous releases include a URL-based programming interface, improved interaction prediction via genomic neighborhood in prokaryotes, and the inclusion of protein structures.
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Uncovering disease-disease relationships through the incomplete interactome
Jörg Menche,Amitabh Sharma,Maksim Kitsak,Maksim Kitsak,Susan Dina Ghiassian,Susan Dina Ghiassian,Marc Vidal,Joseph Loscalzo,Albert-László Barabási +8 more
TL;DR: A network-based framework to identify the location of disease modules within the interactome and use the overlap between the modules to predict disease-disease relationships is presented and it is found that disease pairs with overlapping disease modules display significant molecular similarity, elevated coexpression of their associated genes, and similar symptoms and high comorbidity.
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WebGestalt 2017: a more comprehensive, powerful, flexible and interactive gene set enrichment analysis toolkit
TL;DR: Gene Set Enrichment Analysis and Network Topology-based Analysis have been added to WebGestalt 2017, providing complementary approaches to the interpretation of high-throughput omics data.
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