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Data Integration in the Life Sciences [electronic resource] : 12th International Conference, DILS 2017, Luxembourg, Luxembourg, November 14-15, 2017, Proceedings / edited by Marcos Da Silveira, Cédric Pruski, Reinhard Schneider.

Contributor(s): Material type: TextTextSeries: Lecture Notes in Bioinformatics ; 10649 | Lecture Notes in Computer Science ; 10649Publisher: Cham : Springer International Publishing : Imprint: Springer, 2017Edition: 1st ed. 2017Description: VII, 109 p. 49 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319697512
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 005.74 23
LOC classification:
  • QA76.9.D3
Online resources:
Contents:
Life Science Data Modelling -- Analysing, Indexing, and Querying Life Sciences Datasets -- Annotating, Matching, and Sharing Life Sciences Datasets -- Privacy and Provenance of Life Sciences Datasets.
In: Springer Nature eBookSummary: This book constitutes the proceedings of the 12th International Conference on Data Integration in the Life Sciences, DILS 2017, held in Luxembourg, in November 2017. The 5 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 16 submissions. They cover topics such as: life science data modelling; analysing, indexing, and querying life sciences datasets; annotating, matching, and sharing life sciences datasets; privacy and provenance of life sciences datasets.
Item type: E-BOOKS
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Life Science Data Modelling -- Analysing, Indexing, and Querying Life Sciences Datasets -- Annotating, Matching, and Sharing Life Sciences Datasets -- Privacy and Provenance of Life Sciences Datasets.

This book constitutes the proceedings of the 12th International Conference on Data Integration in the Life Sciences, DILS 2017, held in Luxembourg, in November 2017. The 5 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 16 submissions. They cover topics such as: life science data modelling; analysing, indexing, and querying life sciences datasets; annotating, matching, and sharing life sciences datasets; privacy and provenance of life sciences datasets.

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