127,917 research outputs found
MCMC-ODPR : primer design optimization using Markov Chain Monte Carlo sampling
Background
Next generation sequencing technologies often require numerous primer designs that require good target coverage that can be financially costly. We aimed to develop a system that would implement primer reuse to design degenerate primers that could be designed around SNPs, thus find the fewest necessary primers and the lowest cost whilst maintaining an acceptable coverage and provide a cost effective solution. We have implemented Metropolis-Hastings Markov Chain Monte Carlo for optimizing primer reuse. We call it the Markov Chain Monte Carlo Optimized Degenerate Primer Reuse (MCMC-ODPR) algorithm.
Results
After repeating the program 1020 times to assess the variance, an average of 17.14% fewer primers were found to be necessary using MCMC-ODPR for an equivalent coverage without implementing primer reuse. The algorithm was able to reuse primers up to five times. We compared MCMC-ODPR with single sequence primer design programs Primer3 and Primer-BLAST and achieved a lower primer cost per amplicon base covered of 0.21 and 0.19 and 0.18 primer nucleotides on three separate gene sequences, respectively. With multiple sequences, MCMC-ODPR achieved a lower cost per base covered of 0.19 than programs BatchPrimer3 and PAMPS, which achieved 0.25 and 0.64 primer nucleotides, respectively.
Conclusions
MCMC-ODPR is a useful tool for designing primers at various melting temperatures at good target coverage. By combining degeneracy with optimal primer reuse the user may increase coverage of sequences amplified by the designed primers at significantly lower costs. Our analyses showed that overall MCMC-ODPR outperformed the other primer-design programs in our study in terms of cost per covered base
OntoMaven: Maven-based Ontology Development and Management of Distributed Ontology Repositories
In collaborative agile ontology development projects support for modular
reuse of ontologies from large existing remote repositories, ontology project
life cycle management, and transitive dependency management are important
needs. The Apache Maven approach has proven its success in distributed
collaborative Software Engineering by its widespread adoption. The contribution
of this paper is a new design artifact called OntoMaven. OntoMaven adopts the
Maven-based development methodology and adapts its concepts to knowledge
engineering for Maven-based ontology development and management of ontology
artifacts in distributed ontology repositories.Comment: Pre-print submission to 9th International Workshop on Semantic Web
Enabled Software Engineering (SWESE2013). Berlin, Germany, December 2-5, 201
Study of Tools Interoperability
Interoperability of tools usually refers to a combination of methods and techniques that address the problem of making a collection of tools to work together. In this study we survey different notions that are used in this context: interoperability, interaction and integration. We point out relation between these notions, and how it maps to the interoperability problem.
We narrow the problem area to the tools development in academia. Tools developed in such environment have a small basis for development, documentation and maintenance. We scrutinise some of the problems and potential solutions related with tools interoperability in such environment. Moreover, we look at two tools developed in the Formal Methods and Tools group1, and analyse the use of different integration techniques
Source File Set Search for Clone-and-Own Reuse Analysis
Clone-and-own approach is a natural way of source code reuse for software
developers. To assess how known bugs and security vulnerabilities of a cloned
component affect an application, developers and security analysts need to
identify an original version of the component and understand how the cloned
component is different from the original one. Although developers may record
the original version information in a version control system and/or directory
names, such information is often either unavailable or incomplete. In this
research, we propose a code search method that takes as input a set of source
files and extracts all the components including similar files from a software
ecosystem (i.e., a collection of existing versions of software packages). Our
method employs an efficient file similarity computation using b-bit minwise
hashing technique. We use an aggregated file similarity for ranking components.
To evaluate the effectiveness of this tool, we analyzed 75 cloned components in
Firefox and Android source code. The tool took about two hours to report the
original components from 10 million files in Debian GNU/Linux packages. Recall
of the top-five components in the extracted lists is 0.907, while recall of a
baseline using SHA-1 file hash is 0.773, according to the ground truth recorded
in the source code repositories.Comment: 14th International Conference on Mining Software Repositorie
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