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: 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: 3145
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
A weighted sequence is a string in which a set of characters may appear at each position with respective probabilities of occurrence. Weighted sequences are able to summarize poorly defined short sequences, as well as the profiles of protein families and complete chromosome sequences. Thus it is of biological and theoretical significance to design powerful algorithms on weighted sequences. A common task is to identify repetitive motifs in weighted sequences, with presence probability not less than a given threshold. We define two types of repeats in weighted sequences, called the loose repeats and the strict repeats, respectively, and then attempt to locate these repeats. Using an iterative partitioning technique, we present algorithms for computing all the loose repeats and strict repeats of every length, respectively. Each solution costs O(n(2)) time.
Download full-text PDF |
Source |
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http://dx.doi.org/10.2174/092986610791760324 | DOI Listing |
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