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
Regulation of protein phosphorylation plays an important role in many cellular processes, particularly in signal transduction. Diseases such as cancer and inflammation are often linked to aberrant signaling pathways. Mass spectrometry-based methods allow monitoring the phosphorylation status in an unbiased and quantitative manner. The analysis of this data requires the application of advanced statistical methods, some of which can be borrowed from the gene expression analysis field. Nevertheless, these methods have to be enhanced or complemented by new methods. After reviewing the key concepts of phosphoproteomics and some major data analysis methods, these tools are applied to a real-world data set.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1007/978-1-60761-987-1_3 | DOI Listing |
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