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
Background: Posttranslational modifications of histones influence the structure of chromatine and in such a way take part in the regulation of gene expression. Certain histone modification patterns, distributed over the genome, are connected to cell as well as tissue differentiation and to the adaption of organisms to their environment. Abnormal changes instead influence the development of disease states like cancer. The regulation mechanisms for modifying histones and its functionalities are the subject of epigenomics investigation and are still not completely understood. Text provides a rich resource of knowledge on epigenomics and modifications of histones in particular. It contains information about experimental studies, the conditions used, and results. To our knowledge, no approach has been published so far for identifying histone modifications in text.
Results: We have developed an approach for identifying histone modifications in biomedical literature with Conditional Random Fields (CRF) and for resolving the recognized histone modification term variants by term standardization. For the term identification F1 measures of 0.84 by 10-fold cross-validation on the training corpus and 0.81 on an independent test corpus have been obtained. The standardization enabled the correct transformation of 96% of the terms from training and 98% from test the corpus. Due to the lack of terminologies exhaustively covering specific histone modification types, we developed a histone modification term hierarchy for use in a semantic text retrieval system.
Conclusion: The developed approach highly improves the retrieval of articles describing histone modifications. Since text contains context information about performed studies and experiments, the identification of histone modifications is the basis for supporting literature-based knowledge discovery and hypothesis generation to accelerate epigenomic research.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2648793 | PMC |
http://dx.doi.org/10.1186/1471-2105-10-S1-S28 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!