Bioinformatics The Machine Learning Approach by Sren Baldi Pierre;Brunak

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By Sren Baldi Pierre;Brunak

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Brammen et al. ” (TMF – national medical IT board) [7] as soon as the concept is launched. 4. Discussion As we chose a non-hypothetical approach to scientific problems, the progress of the project will continuously create new scientific questions and problems; new technologies could contribute as well to the scientific work in the laboratories and to the data-management. Therefore, it is a vital requirement to provide the possibility of expanding the database on a basic level. To support this dynamic process, we chose the EAV model which is defined by a flat structure of organization.

For example: there is an inclusion note under E84 Cystic Fibrosis ‘Includes: mucoviscidosis’. 4 Resources from Nucleotide There are descriptive definition, gene mutation types and location, keywords, source organism and its biological hierarchical category, reference related information, chromosome location, map location, molecular types and origin gene sequence. The constraints in the search page of Nucleotide include fields, molecular types, gene location, segmented sequences, source databases, and modification date.

In terms of searching, the qualifiers in EMBL and DDBJ are similar to each other and more specific and detailed than in Nucleotide. For example there are 22 items in molecular types in EMBL’s “Extended Query Form”, 19 in DDBJ’s “Advanced Search Page” and only 3 in Nucleotide. In OMIM, the entry includes ‘authoritative’ [18] textual descriptions for disorders, gene function and genotype/phenotype correlations, and clinical features. Resources in OMIM are different from others in the level of detail for these descriptions.

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