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Artificial Intelligence Methods and Tools for Systems Biology (Computational Biology)
 
 
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Artificial Intelligence Methods and Tools for Systems Biology (Computational Biology) [Paperback]

W. Dubitzky (Editor), Francisco Azuaje (Editor)

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Book Description

March 15, 2005 1402029594 978-1402029592 1

This book provides simultaneously a design blueprint, user guide, research agenda, and communication platform for current and future developments 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 with developing and using AI technologies in the context of life sciences research. As a user guide, this volume addresses the requirements of researchers to gain a basic understanding of key AI methodologies for life sciences research. Its emphasis is not on an intricate mathematical treatment of the presented AI methodologies. Instead, it aims at providing the users with a clear understanding and practical know-how of the methods. As a research agenda, the book is intended for computer and life science students, teachers, researchers, and managers who want to understand the state of the art of the presented methodologies and the areas in which gaps in our knowledge demand further research and development. Our aim was to maintain the readability and accessibility of a textbook throughout the chapters, rather than compiling a mere reference manual. The book is also intended as a communication platform seeking to bride the cultural and technological gap among key systems biology disciplines. To support this function, contributors have adopted a terminology and approach that appeal to audiences from different backgrounds.


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Inside This Book (learn more)
First Sentence:
Thousands of new chemicals are introduced every year in the market for their use in products such as drugs, foods, pesticides, cosmetics, etc. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
generative inverse modeling, predictor set size, cooperative metaheuristics, heterogeneous time series, sentence tokenization, modular competition, neurodynamical model, selective pools, molecular biology domain, chemical ontology, similitude terms, biased competition, theoretical peptide, expression time series, classifier development, predictive toxicology, heteroaromatic amines, protein interaction data, microarray measurements, expression data sets, aminoazo dyes, optimal pathway, mutual entropy, gene ontology, gene expression data
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Pacific Symposium, New York, Chem Inf Comp Sci, Academic Press, Predictive Toxicology of Chemicals, National Library of Medicine, Nature Genetics, Morgan Kaufmann, Nucleic Acids Res, San Diego, Annals of Statistics, Boca Raton, Chem Inf Comput Sci, Genome Res, Journal of Biomedical Informatics, Lawrence Erlbaum Assoc, Medical Subject Headings, Oxford University Press, San Mateo
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