Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Hayai-Annotation, an annotation tool powered by the R-shinydashboard browser interface, implements a workflow that integrates sequence alignment using DIAMOND against UniProtKB Plants and ortholog inference using OrthoLoger. We here propose a pipeline to explore genome evolution and adaptation from a different perspective, by creating a network considering orthologs and gene ontology as nodes, with edges based on the annotation for each gene. This approach aims to improve the visualization of conserved biological processes and functions, highlight species-specific adaptations, and enhance the ability to infer the functions of uncharacterized genes by comparing edge patterns across species. To our knowledge, this is the first attempt to build a network using annotated OrthoDB orthologs and Gene Ontology terms (Molecular Function and Biological Process) as nodes, providing a comprehensive view of gene distribution and function in plant species. The GO annotation accuracy was assessed by the CAFA-evaluator, demonstrating that the accuracy of this version of Hayai-Annotation exceeded that of the benchmark, InterProScan. The updated Hayai-Annotation enhances ortholog analysis functionality, allowing for evolutionary insights from gene sequences, and is expected to contribute significantly to the future development of plant genome analysis.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11742577 | PMC |
http://dx.doi.org/10.1016/j.csbj.2024.12.011 | DOI Listing |