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Artículo
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Pairwise gene GO-based measures for biclustering of high-dimensional expression data
(BMC: part of Springer Verlag, 2018)
Background: Biclustering algorithms search for groups of genes that share the same behavior under a subset of samples in gene expression data. Nowadays, the biological knowledge available in public repositories can be ...
Ponencia
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Virtual Error: A New Measure for Evolutionary Biclustering
(Springer, 2007)
Many heuristics used for finding biclusters in microarray data use the mean squared residue as a way of evaluating the quality of biclusters. This has led to the discovery of interesting biclusters. Recently it has been ...
Ponencia
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Residue-residue Contact Prediction based on Evolutionary Computation
(Springer, 2011)
In this study, a novel residue-residue contacts prediction approach based on evolutionary computation is presented. The prediction is based on four amino acids properties. In particular, we consider the hydrophobicity, ...
Capítulo de Libro
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Discovering decision rules from numerical data streams
(2004)
This paper presents a scalable learning algorithm to classify numerical, low dimensionality, high-cardinality, time-changing data streams. Our approach, named SCALLOP, provides a set of decision rules on demand which ...
Artículo
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Discovery of motifs to forecast outlier occurrence in time series
(Elsevier, 2011)
The forecasting process of real-world time series has to deal with especially unexpected values, commonly known as outliers. Outliers in time series can lead to unreliable modeling and poor forecasts. Therefore, the ...
Artículo
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Projection-based measure for efficient feature selection
(IOS Press, 2002-12-01)
The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant attributes, allow making models of classification simpler and easy to understand. Depending on the ...
Ponencia
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Neighborhood-Based Clustering of Gene-Gene Interactions
(Springer, 2006)
n this work, we propose a new greedy clustering algorithm to identify groups of related genes. Clustering algorithms analyze genes in order to group those with similar behavior. Instead, our approach groups pairs of genes ...
Capítulo de Libro
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Evolutionary segmentation of yeast genome
(2004)
Segmentation algorithms differ from clustering algorithms with regard to how to deal with the physical location of genes throughout the sequence. Therefore, segments have to keep the original positions of consecutive genes, ...
Artículo
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An evolutionary approach to estimating software development projects
(Elsevier, 2001)
The use of dynamic models and simulation environments in connection with software projects paved the way for tools that allow us to simulate the behaviour of the projects. The main advantage of a Software Project Simulator ...