Mutual information estimation reveals global associations between stimuli and biological processes
2009

Understanding How Stimuli Affect Biological Processes

Sample size: 500 publication Evidence: high

Author Information

Author(s): Suzuki Taiji, Sugiyama Masashi, Kanamori Takafumi, Sese Jun

Primary Institution: The University of Tokyo

Hypothesis

Can a new method reveal global changes in biological processes caused by different stimuli?

Conclusion

The study introduced a novel method called LSMI that effectively reveals the global organization of cellular processes in response to various stimuli.

Supporting Evidence

  • The LSMI method can detect nonlinear associations within cellular processes.
  • Non-natural stimuli were found to affect various biological processes significantly.
  • Biological processes can be categorized into four types based on their responses to stimuli.

Takeaway

The researchers created a new way to see how different conditions affect cells, helping us understand how cells work better.

Methodology

The study used a new feature selection method called Least-Squares Mutual Information (LSMI) to analyze gene expression data from yeast under various stimuli.

Limitations

The study may not account for all possible biological processes and relies on the quality of the datasets used.

Participant Demographics

The study focused on yeast as a model organism.

Digital Object Identifier (DOI)

10.1186/1471-2105-10-S1-S52

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