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Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.
Journal of Integrative Bioinformatics
|June 14, 2017
Summary
Bioinformatics tools help scientists prioritize candidate genes from large genetic datasets. These computational approaches integrate diverse biological data, aiding in the discovery of genes influencing traits without adverse effects.
Area of Science:
- Genomics
- Bioinformatics
- Systems Biology
Background:
- Genetics and "omics" studies identify numerous candidate genes for genotype-phenotype relationships.
- Scientists face challenges in manually reviewing vast, heterogeneous biological data from literature and databases.
- Prioritizing causal genes requires efficient integration and evaluation of complex information.
Purpose of the Study:
- To review bioinformatics tools and databases for biological knowledge discovery.
- To highlight methods for prioritizing candidate genes and network components.
- To address the need for computational tools in genetic research.
Main Methods:
- Review of existing bioinformatics tools and databases.
- Discussion of data integration and evaluation strategies.
- Focus on prioritizing genes impacting biological outcomes.
Main Results:
- Several bioinformatics tools and databases are crucial for biological knowledge discovery.
- These tools aid in prioritizing candidate genes from large datasets.
- Computational approaches facilitate the identification of genes for targeted interventions.
Conclusions:
- Bioinformatics tools are essential for navigating complex biological data.
- Effective prioritization of candidate genes requires robust computational support.
- Future challenges include further integration and evaluation of heterogeneous biological information.
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