Data modeling: the key to biological data integration

François Rechenmann 1
1 IBIS - Modeling, simulation, measurement, and control of bacterial regulatory networks
LAPM - Laboratoire Adaptation et pathogénie des micro-organismes [Grenoble], Inria Grenoble - Rhône-Alpes, Institut Jean Roget
Abstract : Page Header Open Journal Systems Journal Help User Username Password Remember me About The Author François Rechenmann Genostar Bioinformatics Solutions, Montbonnot France Article Tools Print this article Indexing metadata How to cite item Finding References Review policy Email this article (Login required) Email the author (Login required) Post a Comment (Login required) Related Items Show all Font Size Make font size smaller Make font size default Make font size larger Journal Content Search Browse By Issue By Author By Title Information For Readers For Authors For Librarians Keywords BITS COST ChIP-seq EMBnet ISCB Italian Bioinformatics Society RIBio RNA-seq SNPs alternative splicing committee report data analysis education gene expression metagenomics miRNAs next generation sequencing node report small RNA structural bioinformatics training Home About Log In Register Search Current Archives Announcements Archives (EMBnet.news) Contact Home > Vol 18 > Rechenmann Data modeling: the key to biological data integration François Rechenmann Abstract Motivation and Objectives The advent of NGS technologies is focusing much of the attention towards the data management issue. However, more than their volume, it is the diversity of biological data which constitutes the real bioinformatics bottleneck; a bottleneck which cannot be solved through technological considerations only, such as cloud infrastructures for instance. A bioinformatics platform must indeed store, organize and give access to a wide span of data and results. First of all, the experimental data and their transformations: not only the sequence data, such as the reads, the assembly files and the resulting contigs - to name the most important ones, but also spectra or metabolic flux measurements. Through the interpretation of these data, biological entities are predicted and characterized: coding regions, regulatory signals, polypeptides, enzymes classes, peptide tags, and so on. All these entities must also be properly described, connected each other and stored in adequately structured data repositories. Conversely, the programs that implement the analysis algorithms must be able to access these data and these entity descriptions to produce new secondary data and predict new entities. In this context, conceptual data modeling appears to be the very first task any project aiming at the design and the development of a bioinformatics integrated platform should perform.
Liste complète des métadonnées

https://hal.inria.fr/hal-00793341
Contributeur : François Rechenmann <>
Soumis le : vendredi 22 février 2013 - 10:21:17
Dernière modification le : jeudi 11 janvier 2018 - 06:22:14

Identifiants

  • HAL Id : hal-00793341, version 1

Collections

Citation

François Rechenmann. Data modeling: the key to biological data integration. EMBnet.journal, EMBnet, 2012, 18, pp.59-60. 〈hal-00793341〉

Partager

Métriques

Consultations de la notice

350