8 research outputs found
Faster Approximate String Matching for Short Patterns
We study the classical approximate string matching problem, that is, given
strings and and an error threshold , find all ending positions of
substrings of whose edit distance to is at most . Let and
have lengths and , respectively. On a standard unit-cost word RAM with
word size we present an algorithm using time When is
short, namely, or this
improves the previously best known time bounds for the problem. The result is
achieved using a novel implementation of the Landau-Vishkin algorithm based on
tabulation and word-level parallelism.Comment: To appear in Theory of Computing System
TagCleaner: Identification and removal of tag sequences from genomic and metagenomic datasets
<p>Abstract</p> <p>Background</p> <p>Sequencing metagenomes that were pre-amplified with primer-based methods requires the removal of the additional tag sequences from the datasets. The sequenced reads can contain deletions or insertions due to sequencing limitations, and the primer sequence may contain ambiguous bases. Furthermore, the tag sequence may be unavailable or incorrectly reported. Because of the potential for downstream inaccuracies introduced by unwanted sequence contaminations, it is important to use reliable tools for pre-processing sequence data.</p> <p>Results</p> <p>TagCleaner is a web application developed to automatically identify and remove known or unknown tag sequences allowing insertions and deletions in the dataset. TagCleaner is designed to filter the trimmed reads for duplicates, short reads, and reads with high rates of ambiguous sequences. An additional screening for and splitting of fragment-to-fragment concatenations that gave rise to artificial concatenated sequences can increase the quality of the dataset. Users may modify the different filter parameters according to their own preferences.</p> <p>Conclusions</p> <p>TagCleaner is a publicly available web application that is able to automatically detect and efficiently remove tag sequences from metagenomic datasets. It is easily configurable and provides a user-friendly interface. The interactive web interface facilitates export functionality for subsequent data processing, and is available at <url>http://edwards.sdsu.edu/tagcleaner</url>.</p
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A multiprocessor parallel approach to bit-parallel approximate string matching
The purpose of this project is to present with empirical results that a parallel design with the use of multiple processors can be successfully applied along with bit-parallel approximate string matching algorithms to solve practical bioinformatics problems. It will demonstrate that nearly optimal speedup can be achieved with a cluster of between two and eight workstations using MPI (Message Passing Interface), directly decreasing the total latency required to perform a string matching problem