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Model, Integrate, Search... Repeat: A Sound Approach to Building Integrated Repositories of Genomic Data 1st ed. 2023 [Mīkstie vāki]

  • Formāts: Paperback / softback, 270 pages, height x width: 235x155 mm, weight: 450 g, 68 Illustrations, black and white; XIX, 270 p. 68 illus., 1 Paperback / softback
  • Sērija : Lecture Notes in Business Information Processing 496
  • Izdošanas datums: 11-Dec-2023
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031449061
  • ISBN-13: 9783031449062
Citas grāmatas par šo tēmu:
  • Mīkstie vāki
  • Cena: 54,05 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Standarta cena: 63,59 €
  • Ietaupiet 15%
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  • Formāts: Paperback / softback, 270 pages, height x width: 235x155 mm, weight: 450 g, 68 Illustrations, black and white; XIX, 270 p. 68 illus., 1 Paperback / softback
  • Sērija : Lecture Notes in Business Information Processing 496
  • Izdošanas datums: 11-Dec-2023
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031449061
  • ISBN-13: 9783031449062
Citas grāmatas par šo tēmu:
This book is a revised version of the PhD dissertation written by the author to receive her PhD from the Department of Electronics, Information and Bioengineering at Politecnico di Milano, Italy.





The work deals with one of the central objectives of the European Research Council project Data-Driven Genomic Computing, i.e., building an integrated repository for genomic data. It reflects the research adventure that starts from modeling biological data, goes through the challenges of integrating complex data and their describing metadata and finally builds tools for searching the data empowered by a semantic layer. The results of this thesis are part of a broad vision: the availability of conceptual models, related databases, and search systems for both humans and viruses genomics will provide important opportunities for research, especially if virus data will be connected to its host, the human being, who is the provider of genomic and phenotype information.







In 2023, the PhD dissertation won the CAiSE PhD Award, granted to outstanding PhD theses in the field of information systems engineering.