دورية أكاديمية
Genetically improved BarraCUDA
| العنوان: | Genetically improved BarraCUDA |
|---|---|
| المؤلفون: | W. B. Langdon, Brian Yee Hong Lam |
| المصدر: | BioData Mining, Vol 10, Iss 1, Pp 1-11 (2017) |
| بيانات النشر: | BMC, 2017. |
| سنة النشر: | 2017 |
| المجموعة: | LCC:Computer applications to medicine. Medical informatics LCC:Analysis |
| مصطلحات موضوعية: | GPGPU, Parallel computing, Genetic improvement, Double-ended DNA sequence, Nextgen NGS, Computer applications to medicine. Medical informatics, R858-859.7, Analysis, QA299.6-433 |
| الوصف: | Abstract Background BarraCUDA is an open source C program which uses the BWA algorithm in parallel with nVidia CUDA to align short next generation DNA sequences against a reference genome. Recently its source code was optimised using “Genetic Improvement”. Results The genetically improved (GI) code is up to three times faster on short paired end reads from The 1000 Genomes Project and 60% more accurate on a short BioPlanet.com GCAT alignment benchmark. GPGPU BarraCUDA running on a single K80 Tesla GPU can align short paired end nextGen sequences up to ten times faster than bwa on a 12 core server. Conclusions The speed up was such that the GI version was adopted and has been regularly downloaded from SourceForge for more than 12 months. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1756-0381 |
| Relation: | http://link.springer.com/article/10.1186/s13040-017-0149-1; https://doaj.org/toc/1756-0381 |
| DOI: | 10.1186/s13040-017-0149-1 |
| URL الوصول: | https://doaj.org/article/2a2f5f172f9d4527aab8020e766f1f44 |
| رقم الأكسشن: | edsdoj.2a2f5f172f9d4527aab8020e766f1f44 |
| قاعدة البيانات: | Directory of Open Access Journals |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 17560381 |
|---|---|
| DOI: | 10.1186/s13040-017-0149-1 |