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: 3122
Function: getPubMedXML
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
1-D and 2-D LC methods were utilized for proteome analysis of undepleted human serum. Separation of peptides in 2-D LC was performed either with strong cation exchange (SCX)-RP chromatography or with an RP-RP 2-D LC approach. Peptides were identified by MS/MS using a data-independent acquisition approach. A peptide retention prediction model was used to highlight the potential false-positive peptide identifications. When applying selected data filtration, we identified 52 proteins based on 316 peptides in serum in 1-D LC setup. One hundred and eighty-four proteins/1036 peptides and 142 proteins/905 peptides were identified in RP-RP and SCX-RP 2-D LC, respectively. The performance of both 2-D LC methods for proteomic analysis is critically compared.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1002/elps.200800630 | DOI Listing |
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