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Linking, Literature, Information, and Knowledge for Biologie [electronic resource] : Workshop of the BioLINK Special Interest Group, ISBM/ECCB 2009, Stockholm, June 28-29, 2009, Revised Selected Papers /

Contributor(s): Material type: TextTextSeries: Lecture Notes in Bioinformatics ; 6004Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010Edition: 1st ed. 2010Description: XII, 81 p. 10 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642131318
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.312 23
LOC classification:
  • QA76.9.D343
Online resources:
Contents:
BioLINK 2009 -- Overview of the Ninth Annual Meeting of the BioLINK SIG at ISMB: Linking Literature, Information and Knowledge for Biology -- Principles of Bioimage Informatics: Focus on Machine Learning of Cell Patterns -- Summary of the BioLINK Special Interest Group Session on the Future of Scientific Publishing -- Structured Literature Image Finder: Extracting Information from Text and Images in Biomedical Literature -- Toward Computer-Assisted Text Curation: Classification Is Easy (Choosing Training Data Can Be Hard...) -- Mining Protein-Protein Interactions from GeneRIFs with OpenDMAP -- Combining Semantic Relations and DNA Microarray Data for Novel Hypotheses Generation -- Learning from Positive and Unlabeled Documents for Retrieval of Bacterial Protein-Protein Interaction Literature -- Extracting and Normalizing Gene/Protein Mentions with the Flexible and Trainable Moara Java Library.
In: Springer Nature eBook
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BioLINK 2009 -- Overview of the Ninth Annual Meeting of the BioLINK SIG at ISMB: Linking Literature, Information and Knowledge for Biology -- Principles of Bioimage Informatics: Focus on Machine Learning of Cell Patterns -- Summary of the BioLINK Special Interest Group Session on the Future of Scientific Publishing -- Structured Literature Image Finder: Extracting Information from Text and Images in Biomedical Literature -- Toward Computer-Assisted Text Curation: Classification Is Easy (Choosing Training Data Can Be Hard...) -- Mining Protein-Protein Interactions from GeneRIFs with OpenDMAP -- Combining Semantic Relations and DNA Microarray Data for Novel Hypotheses Generation -- Learning from Positive and Unlabeled Documents for Retrieval of Bacterial Protein-Protein Interaction Literature -- Extracting and Normalizing Gene/Protein Mentions with the Flexible and Trainable Moara Java Library.

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