Add to ORKGIn this paper, we present a fast and scalable method for computing eigenvector centrality using graphics processing units (GPUs). The method is designed to compute the centrality on gene-expression networks, where the network is pre-constructed in the form of kNN graphs from DNA microarray data sets
Background: The analysis of biological networks has become a major challenge due to the recent devel...
Identification of central genes and proteins in biomolecular networks provides credible candidates f...
The identification of network motifs has important applications in numerous domains, such as pattern...
Research Doctorate - Computer ScienceTHE amount of data in our world has been exploding. Computer-ba...
In this paper, we present graphics processing unit (GPU) based implementations of three popular shor...
<div><p>Gene co-expression networks comprise one type of valuable biological networks. Many methods ...
Gene co-expression networks comprise one type of valuable biological networks. Many methods and tool...
In this paper, we present what we believe to be the first GPU-based implementation (using CUDA) for ...
Recent advances in high-throughput genomic technology, such as micro arrays, usually produce vast am...
Gene co-expression networks comprise one type of valuable biological networks. Many methods and tool...
The biological datasets produced as a result of high-throughput genomic research such as specificall...
Understanding the regulation of gene expression is one of the key problems in current biology. A pro...
The analysis of biological networks has become a major challenge due to the recent development of hi...
The structural analysis of biological networks includes the ranking of the vertices based on the con...
Network alignment is an important bridge to understanding human protein-protein interactions (PPIs) ...
Background: The analysis of biological networks has become a major challenge due to the recent devel...
Identification of central genes and proteins in biomolecular networks provides credible candidates f...
The identification of network motifs has important applications in numerous domains, such as pattern...
Research Doctorate - Computer ScienceTHE amount of data in our world has been exploding. Computer-ba...
In this paper, we present graphics processing unit (GPU) based implementations of three popular shor...
<div><p>Gene co-expression networks comprise one type of valuable biological networks. Many methods ...
Gene co-expression networks comprise one type of valuable biological networks. Many methods and tool...
In this paper, we present what we believe to be the first GPU-based implementation (using CUDA) for ...
Recent advances in high-throughput genomic technology, such as micro arrays, usually produce vast am...
Gene co-expression networks comprise one type of valuable biological networks. Many methods and tool...
The biological datasets produced as a result of high-throughput genomic research such as specificall...
Understanding the regulation of gene expression is one of the key problems in current biology. A pro...
The analysis of biological networks has become a major challenge due to the recent development of hi...
The structural analysis of biological networks includes the ranking of the vertices based on the con...
Network alignment is an important bridge to understanding human protein-protein interactions (PPIs) ...
Background: The analysis of biological networks has become a major challenge due to the recent devel...
Identification of central genes and proteins in biomolecular networks provides credible candidates f...
The identification of network motifs has important applications in numerous domains, such as pattern...