Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes.

By Lude Franke, Harm van Bakel, L. Fokkens, Edwin D. de Jong, Michael Egmont-Petersen, C. Wijmenga. American Journal of Human Genetics, 2006

527 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/6267c09756bbd4e6ae5a32f51cc1c131e42a0218

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Citations in the corpus

Reactome: a knowledge base of biologic pathways and processes (2007, methodology): “More recently, Franke and coworkers [30] used Reactome as the training set for an application that prioritizes genetic association study gene candidate lists.”
Identifying Relationships among Genomic Disease Regions: Predicting Genes at Pathogenic SNP Associations and Rare Deletions (2009, background): “In fact, it is even able to identify relatedness between genes that have no established common pathways or article co-citations! In contrast, other strategies start with static gene relationships—such as (1) preconstructed molecular networks [12,16] or sets of gene with common function [11,15] or (2”
The power of protein interaction networks for associating genes with diseases (2010, unknown): “Several techniques for uncovering gene–disease associations take an integrative approach, leveraging Gene Ontology annotations (Aerts et al., 2006; Franke et al., 2006; Gaulton et al., 2007; Perez-Iratxeta et al., 2007; Radivojac et al., 2008; Sam et al., 2007), gene expression (Aerts et al., 2006;…”
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, background): “Network-based identification of disease biomarkers Network-based identification of disease related geneswas suggested by relatively early studies (Krauthammer et al., 2004; Chen et al., 2006a; Franke et al., 2006; Gandhi et al., 2006; Oti et al., 2006; Xu & Li, 2006).”
Mining breast cancer genes with a network based noise-tolerant approach (2013, background): “…physical attribute-based methods include screening direct neighbors of known disease genes in the PPI network [7,8], comparing shortest path length [9] between candidate genes and known disease genes, clustering or graph partitioning to uncover disease modules in the interaction network [10-12].”
Network-based global inference of human disease genes (2008, methodology): “…Franke et al , 2006), functional annotations (Freudenberg and Propping, 2002; Perez-Iratxeta et al , 2002; Turner et al , 2003; Aerts et al , 2006; Franke et al , 2006), literature descriptions (van Driel et al , 2003; Aerts et al , 2006; Li et al , 2006; Gaulton et al , 2007), physical…”
Network propagation: a universal amplifier of genetic associations (2017, background): “One could then prioritize new genes on the basis of their distance to the prior list 27 ( FIG.”
Enhancing the Prioritization of Disease-Causing Genes through Tissue Specific Protein Interaction Networks (2012, methodology): “These methods are often based on system-wide data such as protein interaction networks [4–9], gene expression [8,10–12], sequence similarity of genes [13,14], functional similarity and annotation [8,12,13] and more (for a review on these methods see [15,16]).”
Prioritizing candidate disease genes by network-based boosting of genome-wide association data. (2011, background): “(A) 21 diverse functional genomic and proteomic data sets (Supplemental Table S1) were evaluated for their tendencies to link genes in the same biological processes.”
Protein networks in disease. (2008, methodology): “Franke et al. (2006) devised the Prioritizer algorithm based on similar principles.”
Network visualization and analysis of gene expression data using BioLayout Express3D (2009, background): “7) is an application designed for displaying network graphs from biologically derived data and is based on an earlier program, BioLayout Java, written in Java and utilizing Java2D for graphics 17,18 .”
Associating Genes and Protein Complexes with Disease via Network Propagation (2010, background): “Such a similarity can be based on sequence [1], functional annotation [2], protein-protein interactions [3,4] and more (see [5] for a comprehensive review of these methods).”
Candidate Causal Regulatory Effects by Integration of Expression QTLs with Complex Trait Genetic Associations (2010, result): “This is in agreement with recent studies reporting that disease causative genes are functionally more closely related [24].”