An intelligent systems for data analysis

In the Perspective of IEEE Intelligent Systems, Altman  stated the following key feature for developing intelligent system for biological data analysis.

Biological data is normally collected with a relatively low signal-to-noise ratio. This creates a need for
robust analysis methods.

Biology theoretical basis is still in its infancy; so few "first principle" approaches have any chance of working yet. This creates a need for statistical and probabilistic models.

Despite the wealth of biological data, biology is still relatively knowledge rich and data poor. We know more about biology in a qualitative sense than a quantitative one. This creates a need for complex knowledge representations.

Biology (and its associated data sources) operate at multiple scales that are tightly linked. This creates a need
for cross-scale data integration methods.

Biological research efforts are distributed, and the associated databases focus on particular types of data. This creates a need for data integration methods.

Biologists think graphically about their work. This creates a need for user interfaces and graphical metaphors
for communicating

 

 

 

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