PASQUIER , Claude

GenMiner is an implementation of association rule discovery dedicated to the analysis of genomic data. It allows the analysis of datasets integrating multiple sources of biological data represented as both discrete values, such as gene annotations, and continuous values, such as gene expression measures. GenMiner implements the new NorDi...

During the last decade, several clustering and association rule mining techniques have been applied to identify groups of co-regulated genes in gene expression data. Nowadays, integrating biological knowledge and gene expression data into a single framework has become a major challenge to improve the relevance of mined patterns and simplify...

GENMINER is a smart adaptation of closed itemsets based association rules extraction to genomic data. It takes advantage of the novel NORDI discretization method and of the JCLOSE algorithm to efficiently generate minimal non-redundant association rules. GENMINER facilitates the integration of numerous sources of biological information such as...

During the last decade, several clustering and association rule mining techniques have been applied to highlight groups of co-regulated genes in gene expression data. Nowadays, integrating these data and biological knowledge into a single framework has become a ma- jor challenge to improve the relevance of mined patterns and simplify their...

GENMINER is a smart adaptation of closed itemsets based association rules extraction to genomic data. It takes advantage of the novel NORDI discretization method and of the CLOSE algorithm to efficiently generate minimal non-redundant association rules. GENMINER facilitates the integration of numerous sources of biological information such as...

Biology has become an enormously data-rich subject. Data is generated in many flavors and follows particularities of the omics perspective adopted along experimental studies. For instance, genomics is the field of study dealing with genomes and it is mostly associated with the static view (the genes and where they are placed along the genome)....

During the last decade, several clustering and association rule mining techniques have been applied to highlight groups of co-regulated genes in gene expression data. Nowadays, integrating these data and biological knowledge into a single framework has become a ma- jor challenge to improve the relevance of mined patterns and simplify their...

Using several analyse techniques for the hierarchical clustering of a SAGE expression dataset of 822 tags from 74 tissue samples (normal and cancer) we show that cleaning the dataset (tags and experiments) is critical and that attribution of a tag to a gene is not easy. Comparison of cancers from various tissues is a difficult task as tissue...

Using several analyse techniques for the hierarchical clustering of a SAGE expression dataset of 822 tags from 74 tissue samples (normal and cancer) we show that cleaning the dataset (tags and experiments) is critical and that attribution of a tag to a gene is not easy. Comparison of cancers from various tissues is a difficult task as tissue...

Biology is now an information-intensive science and various research areas, like molecular biology, evolutionary biology or environmental biology, heavily depend on the availability and the efficient use of information. Data mining, that regroups several techniques for analyzing very large datasets, is used to solve problems in an increasing...

La technologie des biopuces permet de mesurer les niveaux d'expression de milliers de gènes dans différentes conditions biologiques générant ainsi des masses de données à analyser. De nos jours, l'interprétation de ces volumineux jeux de donnés à la lumière des différentes sources d'informations est l'un des principaux défis dans la...