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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Learning Causal Networks from Gene Expression Data

Learning Causal Networks from Gene Expression Data

Ahsan, Nasir

Paperback

Probability & Statistics

ISBN10: 3639197798
ISBN13: 9783639197792
Publisher: Blues Kids Of Amer
Published: Nov 27 2009
Pages: 172
Weight: 0.57
Height: 0.40 Width: 6.00 Depth: 9.00
Language: English
In this work we present a new model for identifying dependencies within a gene regulatory cycle. The model incorporates both probabilistic and temporal aspects, but is kept deliberately simple to make it amenable for learning from the gene expression data of microarray experiments. A key simplifying feature in our model is the use of a compression function for collapsing multiple causes of gene expression into a single cause. This allows us to introduce a learning algorithm which avoids the over-fitting tendencies of models with many parameters. We have validated the learning algorithm on simulated data, and carried out experiments on real microarray data. In doing so, we have discovered novel, yet plausible, biological relationships.

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