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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 ...
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 ...
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 ...
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 ...
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-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 ...