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Identifying disease associated genes by network propagation

Yu Qian, Søren Besenbacher, Thomas Mailund, Mikkel Heide Schierup
2014 BMC Systems Biology  
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

Jung Eun Shim, Insuk Lee
2015 Animal Cells and Systems  
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

Gal Barel, Ralf Herwig
2020 Nucleic Acids Research  
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

Jung Eun Shim, Tak Lee, Insuk Lee
2017 Animal Cells and Systems  
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

Sinan Erten, Gurkan Bebek, Rob M Ewing, Mehmet Koyutürk
2011 BioData Mining  
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

Mi Jin Lee, Kwangho Lee, Jooyoung Lee
2016 International Journal of Digital Contents and Applications for Smart Devices  
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]

Uthsav Chitra, Tae Yoon Park, Benjamin J. Raphael
2022 bioRxiv   pre-print
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

Cui, Srinivasan, Korkin
2019 Genes  
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

Junwei Han, Siyao Liu, Zeguo Sun, Yunpeng Zhang, Fan Zhang, Chunlong Zhang, Desi Shang, Haixiu Yang, Fei Su, Yanjun Xu, Chunquan Li, Huan Ren (+1 others)
2017 Scientific Reports  
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]

Marzia Antonella Scelsi, Valerio Napolioni, Michael D Greicius, Andre Altmann, Alzheimer's Disease Neuroimaging Initiative, Alzheimer's Disease Sequencing Project
2019 bioRxiv   pre-print
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

Marzia Antonella Scelsi, Valerio Napolioni, Michael D. Greicius, Andre Altmann, for the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Alzheimer's Disease Sequencing Project (ADSP), Joerg Stelling
2021 PLoS Computational Biology  
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

Aditya Rao, Thomas Joseph, Vangala G. Saipradeep, Sujatha Kotte, Naveen Sivadasan, Rajgopal Srinivasan, Sujan Mamidi
2020 PLoS ONE  
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]

Hongzhu Cui, Suhas Srinivasan, Dmitry Korkin
2019 bioRxiv   pre-print
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]

Borislav H. Hristov, Bernard Chazelle, Mona Singh
2020 arXiv   pre-print
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

Yoo-Ah Kim, Dong-Yeon Cho, Teresa M. Przytycka, Rachel Karchin
2016 PLoS Computational Biology  
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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