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
Cancer is a complex disease caused by multiple factors including genetic mutations, and environmental factors. Cancer-associated proteins are potential biomarkers or targets for diagnostic and therapeutic interventions in cancer. The Universal Protein Resourse (UniPort) is a well-annotated comprehensive resourse for protein sequence records. In the present study, we performed data mining of Uniprot proteins as a proteomic resource. we generated a catalog of 1653 cancer-associated proteins including 344 secretory proteins and 300 cell surface proteins. Integrated bioinformatic analysis including ontological classification, functional enrichment and pathway construction were performed. These proteins could serve as a reference for further studies to discover cancer targets, and the enriched bioinformatic analysis provides new insights into cancer proteomics research.
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Source |
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http://dx.doi.org/10.3892/or.2012.1714 | DOI Listing |
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