Titlebook: Artificial Intelligence Methods and Tools for Systems Biology; Werner Dubitzky,Francisco Azuaje Book 2004 Springer Science+Business Media

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1568-2684 pments in artificial intelligence (AI) approaches to systems biology. It places an emphasis on the molecular dimension of life phenomena and in one chapter on anatomical and functional modeling of the brain...As design blueprint, the book is intended for scientists and other professionals tasked wit

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Derek D. Turner,Michelle I. Turnerrovide a state of the art overview. We present different possible definitions of ontology, examples of bio-ontologies and their use, formalisms that can be used to represent ontologies as well as tools that support the different stages in the life cycle of an ontology.

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hich the vast complexity and flexibility of life processes emerges. Here we review ways by which artificial intelligence approaches can help gaining a more quantitative understanding of regulatory genetic networks at the systems level.

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interior

Systems Level Modeling of Gene Regulatory Networks,hich the vast complexity and flexibility of life processes emerges. Here we review ways by which artificial intelligence approaches can help gaining a more quantitative understanding of regulatory genetic networks at the systems level.

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Book 2004artificial intelligence (AI) approaches to systems biology. It places an emphasis on the molecular dimension of life phenomena and in one chapter on anatomical and functional modeling of the brain...As design blueprint, the book is intended for scientists and other professionals tasked with developi

Entirety

Lazy Learning for Predictive Toxicology based on a Chemical Ontology,esent chemical compounds, we introduce a new approach based on the chemical nomenclature to represent chemical compounds. In our experiments we show that both models, SAR and ontology-based, have comparable results for the predictive toxicology task.

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