Abstract
Theoretical models and computational algorithms can be trained for analysis of complex pathway data sets specifically in case of diseases including cancer. A well-developed model can also be used to predict the outcomes of various alterations made to the cells and can identify intra-cellular targets for drugs and genetic engineering. Inductive logic programming is one such technique that can be used successfully for modeling and analyzing complex networks. It combines Logic Programming and Machine Learning to predict descriptions from examples and background knowledge.
Original language | English |
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Title of host publication | Pathway Modeling and Algorithm Research |
Publisher | Nova Science Publishers, Inc. |
Pages | 83-92 |
Number of pages | 10 |
ISBN (Print) | 9781611227574 |
State | Published - 2011 |
Externally published | Yes |
Keywords
- Bayes classifier
- Feasibility
- Gene regulatory networks
- Learnabilty
- Logic programming.