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Markov clustering (MCL) is becoming a key algorithm within bioinformatics for determining clusters in networks. However, with increasing vast amount of data on biological networks, performance and scalability issues are becoming a critical limiting factor in applications. Meanwhile, GPU computing, which uses CUDA tool for implementing a massively parallel computing environment in the GPU card, is...
Pairwise statistical significance has been found to be quite accurate in identifying related sequences (homologs), which is a key step in numerous bioinformatics applications. However, it is computational and data intensive, particularly for a large amount of sequence data. To prevent it from becoming a performance bottleneck, we resort to Graphics Processing Units (GPUs) for accelerating the computation...
The massively parallel computing using graphical processing unit (GPU), which based on tens of thousands of parallel threats within hundreds of GPU's streaming processors, has gained broad popularity and attracted researchers in a wide range of application areas from finance, computer aided engineering, computational fluid dynamics, game physics, numerics, science, medical imaging, life science, and...
Multifactor dimensionality reduction (MDR) method has been widely applied to detect gene-gene interactions that are well recognized as playing an important role in understanding complex traits, such as disease susceptibility. However, because of an exhaustive analysis of MDR, the current MDR software has some limitations to be extended to the genome-wide association studies (GWAS) with a large number...
The accuracy of Conditional Random Fields (CRF) is achieved at the cost of huge amount of computation to train model. In this paper we designed the parallelized algorithm for the Gradient Ascent based CRF training methods for biological sequence alignment. Our contribution is mainly on two aspects: 1) We flexibly parallelized the different iterative computation patterns, and the according optimization...
Next-generation, high-throughput sequencers are now capable of producing hundreds of billions of short sequences (reads) in a single day. The task of accurately mapping the reads back to a reference genome is of particular importance because it is used in several other biological applications, e.g., genome re-sequencing, DNA methylation, and ChiP sequencing. On a personal computer (PC), the computationally...
Sequence alignment is one of the most fundamental and important operation in Bioinformatics. Among lots of Sequence alignment tools, Blast is one of the most popular algorithms. In this paper, we describe the primary strategy of a GPU-based parallel computing on Blast program.
The use of Bioinformatic tools in routine clinical diagnostics is still facing a number of issues. The more complex and advanced bioinformatic tools become, the more performance is required by the computing platforms. Unfortunately, the cost of parallel computing platforms is usually prohibitive for both public and small private medical practices. This paper presents a successful experience in using...
The graphics processing unit (GPU) has evolved from being a fixed-function processor with programmable stages into a programmable processor with many fixed-function components that deliver massive parallelism. By modifying the GPU's stream processor to support “general-purpose computation” on the GPU (GPGPU), applications that perform massive vector operations can realize many orders-of-magnitude...
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