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Bioinformatics, target discovery and the pharmaceutical/biotechnology industry
1Inpharmatica, 60 Charlotte Street, London, W1T 2NU, UK. r.fagan@inpharmatica.com
Current Opinion in Molecular Therapeutics
|March 16, 2001
Summary
High-throughput computational methods accelerate the identification of novel therapeutic targets within the human genome. These approaches are crucial for drug discovery and development by analyzing vast genomic data.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- The availability of the human genome draft enables genome-wide mining for therapeutic targets.
- Increasing public genomic annotation data requires efficient analysis methods.
- Identifying protein families on a genome-wide scale is essential for drug discovery.
Purpose of the Study:
- To review algorithmic developments for high-throughput, genome-wide target identification.
- To demonstrate the application of these methods for prioritizing therapeutic targets.
Main Methods:
- Genome-wide mining strategies.
- High-throughput computational approaches.
- Algorithmic development for protein family identification.
Main Results:
- Description of the latest algorithmic developments in the field.
- Guidance on applying these algorithms for target identification and prioritization.
Conclusions:
- Computational approaches are vital for rapid, large-scale identification of therapeutic targets.
- Effective use of algorithms aids in prioritizing targets for pharmaceutical and biotechnology companies.