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NALDC Record Details:

A Parallelized Binary Search Tree

Permanent URL:
http://handle.nal.usda.gov/10113/56695
File:
Download [PDF File]
Abstract:
PTTRNFNDR is an unsupervised statistical learning algorithm that detects patterns in DNA sequences, protein sequences, or any natural language texts that can be decomposed into letters of a finite alphabet. PTTRNFNDR performs complex mathematical computations and its processing time increases when input texts become large. To achieve better speed performance, several strategies were applied in the implementation of the program, including parallel operations of binary search trees. A standard binary search tree is not thread-safe due to its dynamic insertion and deletions. Here, we adjusted the standard binary search tree for parallelized operations to achieve improved performance of the PTTRNFNDR algorithm. The method can be applied to other software platforms to quicken data searching through parallel operations of binary search trees when several conditions are met.
Author(s):
Jian Feng , Daniel Q. Naiman , Bret Cooper
Subject(s):
DNA , algorithms , amino acid sequences , computer software , nucleotide sequences
Source:
Information Technology & Software Engineering 2011 v.1 no.1
Language:
English
Year:
2011
Collection:
Journal Articles, USDA Authors, Peer-Reviewed
Rights:
Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.