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GeneCards: a novel functional genomics compendium with automated data mining and query reformulation support
M Rebhan1, V Chalifa-Caspi, J Prilusky
11Department of Molecular Genetics, 2Department of Biological Services (Bioinformatics Unit) and 3The Genome Center, Weizmann Institute of Science, 76100 Rehovot, Israel.
Bioinformatics (Oxford, England)
|October 28, 1998
Summary
GeneCards is a freely accessible web resource providing integrated information on over 7000 human genes. It simplifies access to complex genomic data, aiding researchers in data analysis and decision-making for various biological studies.
Area of Science:
- Bioinformatics
- Genomics
- Molecular Biology
Background:
- Modern biology increasingly relies on genomic analyses, monitoring thousands of genes simultaneously.
- Efficient access to integrated biomedical information is crucial for data analysis and decision-making in research.
- Discovering knowledge from scattered biomedical resources is challenging and time-consuming.
Purpose of the Study:
- To develop a novel topic-specific overview resource for efficient access to distributed biomedical information.
- To design a database providing integrated gene information for researchers.
Main Methods:
- Developed 'GeneCards', a freely accessible web resource.
- Compiled information for over 7000 human genes using Perl scripts.
- Extracted data automatically from databases like SWISS-PROT, OMIM, Genatlas, and GDB.
- Optimized web interface for human browsing and developed query reformulation algorithms.
Main Results:
- GeneCards provides a hypertext 'card' for each human gene with approved symbols.
- Information includes gene functions in health and disease.
- Facilitates immediate insight into current knowledge about genes.
- Supports large-scale expression studies (e.g., DNA chip technology) by enabling quick access to information on numerous genes.
Conclusions:
- GeneCards offers an efficient solution for accessing distributed biomedical information.
- The resource aids researchers in navigating complex genomic data.
- Optimized displays and query support enhance information retrieval and exploration.