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Clustering task aims at the unsupervised classification of patterns (e.g., observations, data, vec- tors, etc.) in different groups. Clustering problem has been approached from different disciplines during the last years...

El problema del descubrimiento de reglas de asociación radica en la necesidad de descubrir patrones en una base de datos de transacciones conocido como análisis de canasta de mercado, teniendo en cuenta el carácter te...

SUMMARY: We present here Blast2GO (B2G), a research tool designed with the main purpose of enabling Gene Ontology (GO) based data mining on sequence data for which no GO annotation is yet available. B2G joints in one app...

BACKGROUND: Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns a...

In this article, we present FactoMineR an R package dedicated to multivariate data analysis. The main features of this package is the possibility to take into account different types of variables (quantitative or categor...

The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. mice 1.0 introduced predictor selection, pa...

A measure is presented which indicates the similarity of clusters which are assumed to have a data density which is a decreasing function of distance from a vector characteristic of the cluster. The measure can be used t...

MOTIVATION: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated ...

The caret package, short for classification and regression training, contains numerous tools for developing predictive models using the rich set of models available in R. The package focuses on simplifying model training...

We have developed three computer programs for comparisons of protein and DNA sequences. They can be used to search sequence data bases, evaluate similarity scores, and identify periodic structures based on local sequence...

This article describes several features in the MAFFT online service for multiple sequence alignment (MSA). As a result of recent advances in sequencing technologies, huge numbers of biological sequences are available and...

Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today's most rapidly growing technical fields, lying at the intersection of computer science a...

Watershed models are powerful tools for simulating the effect of watershed processes and management on soil and water resources. However, no comprehensive guidance is available to facilitate model evaluation in terms of ...

Multiple imputation by chained equations is a flexible and practical approach to handling missing data. We describe the principles of the method and show how to impute categorical and quantitative variables, including sk...

Summary: After more than fifteen years of existence, the R package ape has continuously grown its contents, and has been used by a growing community of users. The release of version 5.0 has marked a leap towards a modern...

Motivation: Quality control and preprocessing of FASTQ files are essential to providing clean data for downstream analysis. Traditionally, a different tool is used for each operation, such as quality control, adapter tri...

limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for informatio...

Con la búsqueda de reglas de asociación se intenta hallar posibles asociaciones entre ítems. Existen ciertas restricciones, como el soporte mínimo y la confidencia para obtener asociaciones interesantes. Un supuesto ...

Deep learning has revolutionized many machine learning tasks in recent years, ranging from image classification and video processing to speech recognition and natural language understanding. The data in these tasks are t...

Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existin...

The ability to afford decision makers with both accurate and timely consolidated information as well as rapid query response times is the fundamental requirement for the success of a Data Warehouse. To provide fast acces...

"We address aggregate queries over GIS data and moving object data, where non-spatial information is stored in a data warehouse. We propose a formal data model and query language to express complex aggregate queries. Nex...

En esta tesis se caracterizan los procesos de explotación de información asociados a los problemas de inteligencia de negocio: descubrimiento de reglas de comportamiento, descubrimiento de grupos, descubrimiento de atr...

A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. However, in many real-world applications, this...