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
The study of marine microbial ecology has been completely transformed by molecular and genomic data: after centuries of relative neglect, genomics has revealed the surprising extent of microbial diversity and how microbial processes transform ocean and global ecosystems. But the revolution is not complete: major gaps in our understanding remain, and one obvious example is that microbial eukaryotes, or protists, are still largely neglected. Here we examine various ways in which protists might be better integrated into models of marine microbial ecology, what challenges this will present, and why understanding the limitations of our tools is a significant concern. In part this is a technical challenge - eukaryotic genomes are more difficult to characterize - but eukaryotic adaptations are also more dependent on morphology and behaviour than they are on the metabolic diversity that typifies bacteria, and these cannot be inferred from genomic data as readily as metabolism can be. We therefore cannot simply follow in the methodological footsteps of bacterial ecology and hope for similar success. Understanding microbial eukaryotes will require different approaches, including greater emphasis on taxonomically and trophically diverse model systems. Molecular sequencing will continue to play a role, and advances in environmental sequence tag studies and single-cell methods for genomic and transcriptomics offer particular promise.
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Source |
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http://dx.doi.org/10.1016/j.cub.2017.03.075 | DOI Listing |
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