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Identifying disease associated genes by network propagation
2014
BMC Systems Biology
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Permutation is used to select genes that are guilty-by-association and thus consistently obtain high scores after network propagation. ...
Genome-wide association studies have identified many individual genes associated with complex traits. ...
Network Guilt by Association (GBA) is an approach for identifying disease genes based on the observation that similar phenotypes arise from functionally related genes. ...
doi:10.1186/1752-0509-8-s1-s6
pmid:24565229
pmcid:PMC4080512
fatcat:sog6mc2wzfat5odlcxieblssei
Network-assisted approaches for human disease research
2015
Animal Cells and Systems
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The functional interdependence between genes for disease progression has been identified by their connections in gene networks, which enables prediction of novel disease genes based on their connections ...
Disease modules can be identified by subnetworks that are enriched for patientspecific activated or mutated genes. ...
(a) Networks facilitate gene prioritization by network propagation of disease information or by integrating disease-specific data with networks. ...
doi:10.1080/19768354.2015.1074108
fatcat:i6twwyjqefcoxfq5xzrhgradny
NetCore: a network propagation approach using node coreness
2020
Nucleic Acids Research
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Furthermore, NetCore implements a semi-supervised approach to identify phenotype-associated network modules, which anchors the identification of novel candidate genes at known genes associated with the ...
Furthermore, we applied NetCore to identify disease genes and modules for Schizophrenia GWAS data and pan-cancer mutation data. ...
These weights can be used to simply re-rank the genes in order to identify novel disease genes, or as an input for a further module identification step, to identify sub-networks which can then be associated ...
doi:10.1093/nar/gkaa639
pmid:32735660
fatcat:iher2elkkvatbgpwvurxyewtwi
From sequencing data to gene functions: co-functional network approaches
2017
Animal Cells and Systems
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Functional hypotheses can be generated from the network based on (i) network connectivity, (ii) network propagation, and (iii) subnetwork analysis. ...
Because all genes exert their functions through interactions with others, network analysis is a legitimate way to study gene functions. ...
(A) Methods based on network connectivity identify hub genes as essential genes, disease-associated genes by network connections to the DEGs in disease conditions, and disease-associated modules based ...
doi:10.1080/19768354.2017.1284156
pmid:30460054
pmcid:PMC6138336
fatcat:liwamr4w6beunc27fnrdvoam7m
DA DA: Degree-Aware Algorithms for Network-Based Disease Gene Prioritization
2011
BioData Mining
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Motivated by this observation, we propose several statistical adjustment methods to account for the degree distribution of known disease and candidate genes, using a PPI network with associated confidence ...
Conclusions: These results demonstrate the importance of employing accurate statistical models and associated adjustment methods in network-based disease gene prioritization, as well as other network-based ...
This work is supported, in part, by the National Science Foundation (NSF) Award CCF-0953195. This work is also supported, in part, by a Choose Ohio First Scholarship to SE by the State of Ohio. ...
doi:10.1186/1756-0381-4-19
pmid:21699738
pmcid:PMC3143097
fatcat:mbm3x2pth5a5lh6v62eagl2nke
The effect of contents on the understanding about the height of a triangle
2016
International Journal of Digital Contents and Applications for Smart Devices
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Systematic approaches based on the protein-protein interaction network(PPIN) to human disease can be essential for identifying disease modules and pathways, for the characterization of diseaseassociated ...
Here, we demonstrate that patientspecific sensitive drug targets are in proximal network modules from individual genetic variants by using genetic profiles of lung adenocarcinoma(LUAD) reported by The ...
This research was supported by the Bio & Medical Technology Development Program of the NRF funded by the Korean government, MSIP (2016M3A9B6915714). ...
doi:10.21742/ijdcasd.2016.3.2.02
fatcat:djehqko7hvehvavimronr6n4g4
NetMix2: Unifying network propagation and altered subnetworks
[article]
2022
bioRxiv
pre-print
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Furthermore, NetMix2 outperforms other methods at recovering known disease genes in pan-cancer somatic mutation data and in genome-wide association data from multiple human diseases. ...
We derive a subnetwork family which we call the propagation family that approximates the subnetworks ranked highly by network propagation. ...
U.C. is supported by NSF GRFP DGE 2039656. B.J.R. is supported by grant U24CA264027 from the National Cancer Institute (NCI). ...
doi:10.1101/2022.01.31.478575
fatcat:mpby3im3dfbe7bufv5d5fczdu4
Enriching Human Interactome with Functional Mutations to Detect High-Impact Network Modules Underlying Complex Diseases
2019
Genes
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Specifically, our approach incorporates and propagates the functional impact of non-synonymous single nucleotide polymorphisms (nsSNPs) on PPIs to implicate the genes that are most likely influenced by ...
However, carving a disease network module from the whole interactome is a difficult task. ...
Our module detection approach first annotates the network with the functional information from genes and the associated mutations, followed by the network propagation to determine new genes associated ...
doi:10.3390/genes10110933
pmid:31731769
pmcid:PMC6895925
fatcat:hlfpixohdvcwxdmm3fvgwgmbfa
LncRNAs2Pathways: Identifying the pathways influenced by a set of lncRNAs of interest based on a global network propagation method
2017
Scientific Reports
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We used a global network propagation algorithm, random walk with restart (RWR), to calculate the propagation scores of protein-coding genes, which reflect the extent of genes influenced by the lncRNAs. ...
A list of protein-coding genes was formed by ranking the protein-coding genes according to their propagation scores. ...
Kohler et al. used this algorithm to prioritize candidate disease genes by mapping known disease genes to the protein interaction network 32 . ...
doi:10.1038/srep46566
pmid:28425476
pmcid:PMC5397852
fatcat:33pkxarfz5f6pcai3lu2o72gdy
Network propagation of rare mutations in Alzheimer's disease reveals tissue-specific hub genes and communities
[article]
2019
bioRxiv
pre-print
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The result of network propagation is a set of smoothed gene scores used to predict disease status through sparse regression. ...
NETPAGE is based on network propagation, a framework that models information flow on a graph and simulates the percolation of genetic variation through gene networks. ...
NETPAGE 360 leverages the well-known strength of network propagation, combining it with multivariate 361 sparse regression to identify genes robustly associated with a disease phenotype by analysing 362 ...
doi:10.1101/781203
fatcat:vh6nhnap5bc3xij34yhn6rig7y
Network propagation of rare variants in Alzheimer's disease reveals tissue-specific hub genes and communities
2021
PLoS Computational Biology
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The result of network propagation is a set of smoothed gene scores that can be tested for association with disease status through sparse regression. ...
NETPAGE is based on network propagation, a framework that models information flow on a graph and simulates the percolation of genetic variation through tissue-specific gene interaction networks. ...
NETPAGE leverages the well-known strength of network propagation, combining it with multivariate sparse regression to identify genes robustly associated with a disease phenotype by analysing the genome-wide ...
doi:10.1371/journal.pcbi.1008517
pmid:33411734
fatcat:6aopcqqhvvfjrh3mpqzrferunu
PRIORI-T: A tool for rare disease gene prioritization using MEDLINE
2020
PLoS ONE
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We extracted rare disease correlation pairs involving diseases, phenotypes and genes from MEDLINE abstracts and used the information propagation algorithm GCAS to build an association network. ...
We built a tool called PRIORI-T for rare disease gene prioritization that uses this network for phenotype-driven rare disease gene prioritization. ...
The Rare Disease Annotator identified 6282 diseases, 8043 phenotypes and 14,430 genes in these 2.4 million abstracts. d) Construction of initial correlation network (ICN) and association network (ASN). ...
doi:10.1371/journal.pone.0231728
pmid:32315351
fatcat:ifrga5d7fnh5dnttqtkonzsnrm
Enriching human interactome with functional mutations to detect high-impact network modules underlying complex diseases
[article]
2019
bioRxiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Specifically, our approach incorporates and propagates the functional impact of non-synonymous single nucleotide polymorphisms (nsSNPs) on PPIs to implicate the genes that are most likely influenced by ...
) network to improve disease module detection. ...
Our module detection approach first annotates the network with the functional information from the genes and associated mutations followed by the network propagation to determine new genes associated with ...
doi:10.1101/786798
fatcat:2f6w7s76szebthtrqdzf7f53zq
A guided network propagation approach to identify disease genes that combines prior and new information
[article]
2020
arXiv
pre-print
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Overall, our work suggests that guided network propagation approaches that utilize both prior and new data are a powerful means to identify disease genes. ...
Previously, network propagation approaches have spread signal across the network from either known disease genes or genes that are newly putatively implicated in the disease (e.g., found to be mutated ...
While initial network approaches to identify disease genes focused on propagating knowledge from a set of known "gold standard" disease genes, with the widespread availability of cancer sequencing data ...
arXiv:2001.06135v1
fatcat:2g54dsxrxbairgi3z4qclydixe
Understanding Genotype-Phenotype Effects in Cancer via Network Approaches
2016
PLoS Computational Biology
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Indeed, network-centric approaches have proven to be helpful for finding genotypic causes of diseases, classifying disease subtypes, and identifying drug targets. ...
Cancer is now increasingly studied from the perspective of dysregulated pathways, rather than as a disease resulting from mutations of individual genes. ...
[81] constructed a human disease network by first creating a bipartite graph based on disease-gene associations and then connecting diseases if they share the same disease genes (Fig 2B) . ...
doi:10.1371/journal.pcbi.1004747
pmid:26963104
pmcid:PMC4786343
fatcat:p2zqfax3gfag7jutp3tq52tqve
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