SYMBIOmatics: synergies in Medical Informatics and Bioinformatics--exploring current scientific literature for emerging topics. Review uri icon

Overview

MeSH

  • Forecasting
  • Systems Integration

MeSH Major

  • Biotechnology
  • Computational Biology
  • Medical Informatics
  • Natural Language Processing
  • Periodicals as Topic
  • Science
  • Technology Assessment, Biomedical

abstract

  • The SYMBIOmatics Specific Support Action (SSA) is "an information gathering and dissemination activity" that seeks "to identify synergies between the bioinformatics and the medical informatics" domain to improve collaborative progress between both domains (ref. to http://www.symbiomatics.org). As part of the project experts in both research fields will be identified and approached through a survey. To provide input to the survey, the scientific literature was analysed to extract topics relevant to both medical informatics and bioinformatics. This paper presents results of a systematic analysis of the scientific literature from medical informatics research and bioinformatics research. In the analysis pairs of words (bigrams) from the leading bioinformatics and medical informatics journals have been used as indication of existing and emerging technologies and topics over the period 2000-2005 ("recent") and 1990-1990 ("past"). We identified emerging topics that were equally important to bioinformatics and medical informatics in recent years such as microarray experiments, ontologies, open source, text mining and support vector machines. Emerging topics that evolved only in bioinformatics were system biology, protein interaction networks and statistical methods for microarray analyses, whereas emerging topics in medical informatics were grid technology and tissue microarrays. We conclude that although both fields have their own specific domains of interest, they share common technological developments that tend to be initiated by new developments in biotechnology and computer science.

publication date

  • March 8, 2007

has subject area

  • Biotechnology
  • Computational Biology
  • Forecasting
  • Medical Informatics
  • Natural Language Processing
  • Periodicals as Topic
  • Science
  • Systems Integration
  • Technology Assessment, Biomedical

Research

keywords

  • Journal Article
  • Meta-Analysis
  • Review

Identity

Language

  • eng

PubMed Central ID

  • PMC1885847

Digital Object Identifier (DOI)

  • 10.1186/1471-2105-8-S1-S18

PubMed ID

  • 17430562

Additional Document Info

start page

  • S18

volume

  • 8 Suppl 1