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
Microbial enzymes have many known applications as biocatalysts. However, only a few of them are currently employed for biocatalysis even though an annotated collection of more than 190 billion bases is available in metagenome sequence databases from uncultured and highly diverse microbial populations. This review aims at providing conceptual and technical bases for the translation of metagenome data into both experimental and computational frameworks that facilitates a comprehensive analysis of the biocatalysts diversity space. We will also briefly present the status of the current capabilities that assess and predict catalytic potential of environmental sites and track its diversity and evolution in large-scale biocatalysis process resulting from studies applying metagenomics in association with gene fingerprinting, catabolic arrays and complementary '-omics'.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1016/j.copbio.2010.09.006 | DOI Listing |
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