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
Promoters contain a large number of binding sites for transcriptional factors transmitting signals from a variety of cellular pathways. The promoter processes these input signals and sets the level of gene expression, the output of the gene. Here, we describe how to design genetic constructs and measure gene expression to deliver data suitable for quantitative analysis. Synthetic genetic constructs are well suited to precisely control and measure gene expression to construct cis-regulatory input functions. These functions can be used to predict gene expression based on signal intensities transmitted to activators and repressors in the gene regulatory region. Simple models of gene expression are presented for competitive and noncompetitive repressions. Complex phenomena, exemplified by synergistic silencing, are modeled by reaction-diffusion equations.
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Source |
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http://dx.doi.org/10.1007/978-1-61779-086-7_3 | DOI Listing |
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