Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Array comparative genomic hybridization (aCGH) provides a genome-wide technique for identifying chromosomal aberrations in human diseases, including cancer. Chromosomal aberrations in cancers are defined as regions that contain an increased or decreased DNA copy number, relative to normal samples. The identification of genomic regions associated with systematic aberrations provides insights into initiation and progression of cancer, and improves diagnosis, prognosis, and therapy strategies. The McNemar test can be used to detect differentially expressed genes after discretization of gene expressions in a microarray experiment for the matched dataset. In this study, we propose a method to detect significantly altered DNA regions, shifted McNemar test, which is based on the standard McNemar test and takes into account changes in copy number variations and the region size throughout the whole genome. In addition, this novel method can be used to detect genomic regions associated with the progress of oral squamous cell carcinoma (OSCC). The performance of the proposed method was evaluated based on the homogeneity within the selected regions and the classification accuracies of the selected regions. This method might be useful for identifying new candidate genes that neighbor known genes based on the whole-genomic variation because it detects significant chromosomal regions, not independent probes.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1007/s11517-010-0595-0 | DOI Listing |
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