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ScalaParBiBit: Scaling the Binary Biclustering in Distributed-Memory Systems
(SpringerLink, 2021-03-19)
[Abstract] Biclustering is a data mining technique that allows us to find groups of rows and columns that are highly correlated in a 2D dataset. Although there exist several software applications to perform biclustering, ...
Parallel definition of tear film maps on distributed-memory clusters for the support of dry eye diagnosis
(Elsevier Ireland Ltd., 2017)
[Abstract] Background and objectives
The analysis of the interference patterns on the tear film lipid layer is a useful clinical test to diagnose dry eye syndrome. This task can be automated with a high degree of accuracy ...
Parallel and Scalable Short-Read Alignment on Multi-Core Clusters Using UPC++
(Johannes Gutenberg University Mainz, 2016)
[Abstract]: The growth of next-generation sequencing (NGS) datasets poses a challenge to the alignment of reads to reference genomes in terms of alignment quality and execution speed. Some available aligners have been shown ...
A general and efficient divide-and-conquer algorithm framework for multi-core clusters
(SpringerLink, 2017)
[Abstract]Divide-and-conquer is one of the most important patterns of parallelism, being applicable to a large variety of problems. In addition, the most powerful parallel systems available nowadays are computer clusters ...
Parallel-FST: A feature selection library for multicore clusters
(Elsevier, 2022-11)
[Abstract]: Feature selection is a subfield of machine learning focused on reducing the dimensionality of datasets by performing a computationally intensive process. This work presents Parallel-FST, a publicly available ...
Fast search of third-order epistatic interactions on CPU and GPU clusters
(Sage Publications Ltd., 2019-05-27)
[Abstract]
Genome-Wide Association Studies (GWASs), analyses that try to find a link between a given phenotype (such as a disease) and genetic markers, have been growing in popularity in the recent years. Relations between ...
An Efficient Ant Colony Optimization Framework for HPC Environments
(Elsevier, 2022)
[Abstract] Combinatorial optimization problems arise in many disciplines, both in the basic sciences and in applied fields such as engineering and economics. One of the most popular combinatorial optimization methods is ...
Parallel ant colony optimization for the training of cell signaling networks
(Elsevier, 2022)
[Abstract]: Acquiring a functional comprehension of the deregulation of cell signaling networks in disease allows progress in the development of new therapies and drugs. Computational models are becoming increasingly popular ...
Parallel feature selection for distributed-memory clusters
(2019)
[Abstract]: Feature selection is nowadays an extremely important data mining stage in the field of machine learning due to the appearance of problems of high dimensionality. In the literature there are numerous feature ...
parSRA: A framework for the parallel execution of short read aligners on compute clusters
(2018)
[Abstract]: The growth of next generation sequencing datasets poses as a challenge to the alignment of reads to reference genomes in terms of both accuracy and speed. In this work we present parSRA, a parallel framework ...