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.
journal_name
Am J Hum Genetjournal_title
American journal of human geneticsauthors
Köhler S,Bauer S,Horn D,Robinson PNdoi
10.1016/j.ajhg.2008.02.013subject
Has Abstractpub_date
2008-04-01 00:00:00pages
949-58issue
4eissn
0002-9297issn
1537-6605pii
S0002-9297(08)00172-9journal_volume
82pub_type
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journal_title:American journal of human genetics
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pub_type: 历史文章,杂志文章
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journal_title:American journal of human genetics
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doi:10.1016/j.ajhg.2011.07.023
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journal_title:American journal of human genetics
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更新日期:1993-03-01 00:00:00
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journal_title:American journal of human genetics
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journal_title:American journal of human genetics
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journal_title:American journal of human genetics
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