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Genome Analysis of Species of Agricultural Interest

  • Maria Luisa Chiusano
  • Nunzio D’Agostino
  • Amalia Barone
  • Domenico Carputo
  • Luigi Frusciante
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 25)

Abstract

In recent years, the role ofbioinformatics in supporting structural and functional genomics and the analysis of the molecules that are expressed in a cell has become fundamental for data management, interpretation, and modeling. This interdisciplinary research area provides methods that aim not only to detect and to extract information from a massive quantity of data but also to predict the structure and function of biomolecules and to model biological systems of small and medium complexity. Although bioinformatics provides a major support for experimental practice, it mainly plays a complementary role in scientific research. Indeed, bioinformatics methods are typically appropriate for large-scale analyses and cannot be replaced with experimental approaches. Specialized databases, semiautomated analyses, and data mining methods are powerful tools in performing large-scale analyses aiming to (i) obtain comprehensive collections; (ii) manage, classify, and explore the data as a whole; and (iii) derive novel features, properties, and relationships. Such methods are thus suitable for providing novel views and supporting in-depth understanding of biological system behavior and designing reliable models.

The success of bioinformatics approaches is directly dependent on the efficiency of data integration and on the value-added information that it produces. This is, in turn, determined by the diversity of data sources and by the quality of the annotation they are endowed with. To fulfill these requirements, we designed the computational platform ISOLA, in the framework of the International Solanaceae Genomics Project. ISOLA is an Italian genomics resource dedicated to the Solanaceae family and was conceived to collect data produced by ‘omics' technologies. Its main features and tools are presented and discussed as an example of how to convert experimental data into biological information that in turn is the basis for modeling biological systems.

Keywords

Genome Browser Gene Predictor Tomato Genome Tentative Consensus Sequence Solanaceae Species 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

We wish to thank Prof. Gerardo Toraldo for useful discussions and constant support. This is the contribution DISSPAPA book 3. Part of the presented work is supported by the Agronanotech Project (Ministry of Agriculture, Italy) and by the PRIN 2006 (Ministry of Scientific Research, Italy) and is in the frame of the EU-SOL Project (European Community).

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Maria Luisa Chiusano
    • 1
  • Nunzio D’Agostino
  • Amalia Barone
  • Domenico Carputo
  • Luigi Frusciante
  1. 1.Department of Soil, Plant, Environmental and Animal Production SciencesUniversity of Naples Federico IINaplesItaly

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