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Related Concept Videos

Statistical Analysis: Overview01:11

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When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
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Related Experiment Video

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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Mining the literature: new methods to exploit keyword profiles.

Miguel A Andrade-Navarro1

  • 1Max Delbrück Center for Molecular Medicine, Robert-Rössle-Str. 10, 13125, Berlin, Germany.

Genome Medicine
|November 2, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a method using Medical Subject Headings (MeSH) profiles to define concepts within biomedical literature. This approach facilitates the discovery of novel associations, such as links between genes and inherited diseases.

Keywords:
Data miningdatabasesdiseasedrugsgenes

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Area of Science:

  • Biomedical Informatics
  • Computational Biology
  • Medical Subject Headings (MeSH)

Background:

  • PubMed database uses curated Medical Subject Headings (MeSH) to annotate biomedical literature.
  • MeSH terms provide a structured summary of article content.
  • Existing methods lack efficient ways to define concepts based on literature.

Purpose of the Study:

  • To present a novel method for generating MeSH term profiles for sets of bibliographic records.
  • To demonstrate how these profiles can define concepts within biomedical literature.
  • To enable the discovery of new associations between biological entities and diseases.

Main Methods:

  • Generating MeSH term profiles for selected bibliographic records.
  • Utilizing these profiles to computationally define specific concepts.
  • Relating concepts based on their MeSH profiles.

Main Results:

  • Successfully defined concepts using MeSH term profiles.
  • Demonstrated the ability to relate concepts through their profiles.
  • Showcased potential for identifying novel gene-disease associations.

Conclusions:

  • MeSH term profiling offers a robust method for concept definition in biomedical literature.
  • This approach enhances literature-based discovery.
  • It holds promise for advancing research in areas like genetics and disease association studies.