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Parallel classification and feature selection in microarray data using SPRINT
- Lawrence Mitchell,
- Terence M. Sloan,
- Muriel Mewissen,
- Peter Ghazal,
- Thorsten Forster,
- Michal Piotrowski,
- Arthur Trew
The statistical language R is favoured by many biostatisticians for processing microarray data. In recent times, the quantity of data that can be obtained in experiments has risen significantly, making previously fast analyses time consuming or even not ...
Adapting bioinformatics applications for heterogeneous systems: a case study
The advent of new sequencing technologies has generated extremely large amounts of information. To successfully apply bioinformatics tools to such large datasets, they need to exhibit scalability and ideally elasticity in diverse computing environments. ...
Hierarchical MapReduce: towards simplified cross-domain dataprocessing
The MapReduce programming model has proven useful for data-driven high throughput applications. However, the conventional MapReduce model limits itself to scheduling jobs within a single cluster. As job sizes become larger, single-cluster solutions grow ...
Advancing next-generation sequencing data analytics with scalable distributed infrastructure
With the emergence of popular next-generation sequencing NGS-based genome-wide protocols such as chromatin immunoprecipitation followed by sequencing ChIP-Seq and RNA-Seq, there is a growing need for research and infrastructure to support the ...
High-throughput virtual molecular docking with AutoDockCloud
Virtual molecular docking is a computational method used in computer-aided drug discovery that calculates the binding affinity of a small molecule drug candidate to a target protein. High-throughput virtual screenings calculate the binding affinities ...
Answering the demands of digital genomics
The continuing revolution in DNA sequencing and biological sensor technologies is driving a digital transformation to our approaches for observation, experimentation, and interpretation that form the foundation of modern biology and genomics. Whereas ...
Array languages and the N-body problem
This paper is a description of the contributions to the Scottish Informatics and Computer Science Alliance Multi-core Challenge on many body planetary simulation made by a compiler group at the University of Glasgow. Our group is part of the Computer ...
SaC/C formulations of the all-pairs N-body problem and their performance on SMPs and GPGPUs
This paper describes our experience in implementing the classical N-body algorithm in SaC and analysing the runtime performance achieved on three different machines: a dual-processor 8-core Dell PowerEdge 2950 a Beowulf cluster node, the reference ...
N-body computations using skeletal frameworks on multicore CPU/graphics processing unit architectures: an empirical performance evaluation
With the emergence of general-purpose computation on graphics processing units, high-level approaches that hide the conceptual complexity of the low-level Compute Unified Device Architecture and Open Computing Language platforms are the subject of ...
Parallel Haskell implementations of the N-body problem
This paper provides an assessment of high-level parallel programming models for multi-core programming by implementing two versions of the n-body problem. We compare three different parallel programming models on the basis of parallel Haskell, differing ...
