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
In the continuing quest to relate microbial communities in bioreactors to function and environmental and operational conditions, engineers and biotechnologists have adopted the latest molecular and 'omic methods. Despite the large amounts of data generated, gaining mechanistic insights and using the data for predictive and practical purposes is still a huge challenge. We present a methodological framework that can guide experimental design, and discuss specific issues that can affect how researchers generate and use data to elucidate the relationships. We also identify, in general terms, bioreactor research opportunities that appear promising.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.copbio.2015.02.002 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!