The Gene Interaction Miner: a new tool for data mining contextual information for protein-protein interaction analysis. (41/1202)

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Mining regulatory 5'UTRs from cDNA deep sequencing datasets. (42/1202)

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Contribution of genomics to the understanding of physiological functions. (43/1202)

Genomics has brought with it a true biological revolution and can be applied to all areas of life sciences. The advent of genomics is thus linked to the development of high-throughput techniques which allows the genome of organisms as a whole to be studied. The first high-throughput techniques to be developed were sequencing methods. These advances will allow new approaches to a variety of problems in biology. For instance, the emerging fields of genomic medicine in humans and genomic selection in livestock are promising. After the sequencing of genomes, genomics has shifted to the study of gene expression and function. This is called the "post-genomic area" by some authors or "functional genomics" by others. The most recent "omics" to be developed are associated with the study of the metabolism (e.g. metabolomics). Integrative "omics" approaches (e.g. nutrigenomics) are based on the association of the omics tools at different levels (DNA, RNA, proteins, metabolites) for a specific objective (here nutrition). In terms of perspectives, it is likely that methods for collecting data will outstrip our capacity to adequately analyse these data. So scientists must develop bioinformatic tools and methods to overcome this difficulty. In addition, high-throughput techniques need to be developed in physiology in order to match the increasing amount of genomic information with true biological data. Finally, there is no doubt that all these new approaches will allow important new genes and novel biological mechanisms to be discovered. Physiological models with invalidated or over-expressed genes will be precious tools to check these new biological discoveries.  (+info)

The PeptideAtlas Project. (44/1202)

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AtMetExpress development: a phytochemical atlas of Arabidopsis development. (45/1202)

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Exploratory data mining analysis identifying subgroups of patients with depression who are at high risk for suicide. (46/1202)

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Data mining of enzymes using specific peptides. (47/1202)

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Altered gene expression in morphologically normal epithelial cells from heterozygous carriers of BRCA1 or BRCA2 mutations. (48/1202)

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