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Acceleration of a Feature Selection Algorithm Using High Performance Computing
(MDPI AG, 2020-09-01)
[Abstract]
Feature selection is a subfield of data analysis that is on reducing the dimensionality of datasets, so that subsequent analyses over them can be performed in affordable execution times while keeping the same ...
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, ...
Fault tolerance of MPI applications in exascale systems: The ULFM solution
(Elsevier BV * North-Holland, 2020-05)
[Abstract]
The growth in the number of computational resources used by high-performance computing (HPC) systems leads to an increase in failure rates. Fault-tolerant techniques will become essential for long-running ...
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 ...
MPI-dot2dot: A Parallel Tool to Find DNA Tandem Repeats on Multicore Clusters
(Springer, 2022)
[Abstract] Tandem Repeats (TRs) are segments that occur several times in a DNA sequence, and each copy is adjacent to other. In the last few years, TRs have gained significant attention as they are thought to be related ...
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 ...
pRIblast: A highly efficient parallel application for comprehensive lncRNA–RNA interaction prediction
(Elsevier, 2023-01)
[Abstract]: Long non-coding RNAs (lncRNAs) play a key role in several biological processes and scientists are constantly trying to come up with new strategies to elucidate their functions. One common approach to characterize ...
Fiuncho: a program for any-order epistasis detection in CPU clusters
(Springer, 2022)
[Abstract]: Epistasis can be defined as the statistical interaction of genes during the expression of a phenotype. It is believed that it plays a fundamental role in gene expression, as individual genetic variants have ...
ParRADMeth: Identification of Differentially Methylated Regions on Multicore Clusters
(IEEE, 2023)
[Abstract]: The discovery of Differentially Methylated (DM) regions is an important research field in biology, as it can help to anticipate the risk of suffering from specific diseases. Nevertheless, the high computational ...