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
Historically, bacterial natural products have served as an excellent source of drug leads, however, in recent decades the rate of discovery has slowed due to multiple challenges. Rapid advances in genome sequencing science in recent years have revealed the vast untapped encoded potential of bacteria to make natural products. To access these molecules, researchers can employ the ever-growing array of bioinformatic tools at their disposal and leverage newly developed experimental approaches to validate these bioinformatic-driven hypotheses. When used together effectively, bioinformatic and experimental tools enable researchers to deeply examine the full diversity of bacterial natural products. This review briefly outlines recent bioinformatic tools that can facilitate natural product research in bacteria including the use of CRISPR, co-occurrence network analysis, and combinatorial generation of microbial natural products to test bioinformatic hypotheses in the lab.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1016/j.cbpa.2023.102367 | DOI Listing |
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