Network-based methods for human disease gene prediction.

By Xiujuan Wang, Natali Gulbahce, Haiyuan Yu. 2011

227 citations recorded by the source corpus.

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In Molecular Biology

Citations in the corpus

EgoNet: identification of human disease ego-network modules (2014, background): “An important property of disease genes in a molecular network is that the nodes with much higher degrees of linkages, so called hubs, should typically be associated with disease genes [19].”
Integrated interactions database: tissue-specific view of the human and model organism interactomes (2015, background): “Known PPI networks have proven valuable for many applications, including prediction of gene function (1,2), identification of disease genes (3,4) and drug discovery (5,6).”
Three-dimensional reconstruction of protein networks provides insight into human genetic disease (2012, unknown): “Earlier implementations of this idea had a significant impact and led to the determination of important disease associations for genes 38 .”
Mining breast cancer genes with a network based noise-tolerant approach (2013, background): “Currently, not all genes have yet been detected even for those diseases whose molecular mechanisms are partially known [1], for instance, breast cancer [2].”
Simplicial closure and higher-order link prediction (2018, background): “Link prediction also has a number of direct applications that cut across disciplines, including predicting friendships in social networks (38), inferring new relationships between genes and diseases (39), and suggesting novel connections in the scientific community (40).”
Methods for the integration of multi-omics data: mathematical aspects (2016, background): “Methods that simulate the diffusion of information throughout a network are being increasingly used, since they allow to study how the information (e.g. differential expression, sequence variations) initially available in one or more network components (vertexes) affects other network regions [42].”
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, methodology): “In the last few years several network-based methods have been developed helping the identification of genes related to a particular disease as reviewed by the excellent summaries of Wang et al. (2011a) and Doncheva et al. (2012a).”