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The methods of combining GWAS and PPI networks mainly fall into two categories, (1) dense module search algorithms in search of significantly enriched subnetworks [ 11, 12, 25], (2) propagation algorithms related to Google's PageRank [ 13, 14] in search of genes that have top ranks in the network.
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We proposed an efficient network-assisted framework to identify candidate genes from GWAS data based on dense module search algorithm.
For genome-wide association studies (GWAS), Jia and Zhao [ 9] applies a dense module search algorithm for locating network modules that are jointly associated with a disease.
In this study, we proposed an alternative restricted search approach based on our previously developed dense module search algorithm, and we demonstrated it in the CATIE GWAS dataset for schizophrenia.
Based on "Network-assisted causal gene detection in genome-wide association studies: an improved module search algorithm", by Peilin Jia and Zhongming Zhao which appeared in Genomic Signal Processing and Statistics (GENSIPS), 2011 IEEE International Workshop on.
Naturally, it is worth examining the relative performance of the search based on modules, as in the case of the pathway search algorithms.
These theorems relate to the efficiency of different "search algorithms".
It already includes personal search history in its search algorithms.
Three search algorithms were introduced during this class: sequential search, binary search, and hash search.
First, competitors argue that Google rigs its search algorithms to demote listings for competing search engines.
Humans built and maintain Facebook's newsfeed algorithm, just as humans built and maintain Google's search algorithms".
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