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Genomic Databanks for Biomedical Informatics

Genomic Databanks for Biomedical Informatics
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Author(s): Andrea Maffezzoli (Politecnico di Milano, Italy)and Marco Masseroli (Politecnico di Milano, Italy)
Copyright: 2008
Pages: 10
Source title: Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Vijayan Sugumaran (Oakland University, Rochester, USA)
DOI: 10.4018/978-1-59904-941-0.ch045

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Abstract

In the area of medical informatics, the recent ICT (information and communication technology) tools and systems supporting knowledge on sciences involved in the study of genes, chromosomes, and protein’s expression level in various organisms, that is genomics and proteomics, are becoming necessary to develop new prospects for the comprehension of mechanisms lying at the base of biological processes which cause a disease. This can allow more effective diagnostic and treatment methods and also personalized pharmacological therapies. At this purpose, the mutual intervention of different sciences, such as biology, medicine, engineering, informatics and mathematics, becomes an indispensable step: The development of a science embracing all these fields is identified in bioinformatics, which was conceived for the analysis, storage and processing of huge amount of biological data. The achievement of all the aforementioned operations involves the creation of the so-called genomic or proteomic databanks, which represent a major source of information on nucleotide sequences, as well as biological, clinical, physiological and bibliographical annotations related to singular sequences. There are different types of databanks based on their peculiar characteristics and features (such as primary and derivative or specialized databanks), and several ways to access data stored in these databanks; there are also specific bioinformatics databank-based tools developed to perform searching operations and to extract significant information, in order to summarize and compare gene annotations related to the causes of a disease and finally to identify a list of the most significant genes as cause of disease.

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