ArticleBioMed research international2014
Local alignment tool based on Hadoop framework and GPU architecture.
Article in BioMed research international, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges.Computational and structural biotechnology journal · 2017Review
- G2LC: Resources Autoscaling for Real Time Bioinformatics Applications in IaaS.Computational and mathematical methods in medicine · 2015Article
- Evaluating the Cassandra NoSQL Database Approach for Genomic Data Persistency.International journal of genomics · 2015Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the rapid growth of next generation sequencing technologies, such as Slex, more and more data have been discovered and published. To analyze such huge data the computational performance is an important issue. Recently, many tools, such as SOAP, have been implemented on Hadoop and GPU parallel computing architectures. BLASTP is an important tool, implemented on GPU architectures, for biologists to compare protein sequences. To deal with the big biology data, it is hard to rely on single GPU. Therefore, we implement a distributed BLASTP by combining Hadoop and multi-GPUs. The experimental results present that the proposed method can improve the performance of BLASTP on single GPU, and also it can achieve high availability and fault tolerance.
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Registered trials
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