Advancing post-genome data and system integration through machine learning
2001
Advancing Post-Genome Data Integration with Machine Learning
publication
Author Information
Author(s): Francisco Azuaje
Primary Institution: University of Dublin - Trinity College
Conclusion
The paper discusses the potential of artificial intelligence and data mining techniques to support the integration of biological data in the post-genome era.
Supporting Evidence
- Artificial intelligence and data mining techniques can analyze multiple sources of biological data.
- Agent-based technologies may improve cooperation capabilities in knowledge discovery.
- XML has become an important choice for data representation and exchange in biotechnology.
Takeaway
This study talks about using smart computer programs to help scientists connect and understand a lot of biological information better.
Limitations
The review is not comprehensive due to space constraints and the growing number of concepts under development.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website