Artificial Intelligence Methods and Tools for Systems Biology: Computational Biology, cartea 5
Editat de W. Dubitzky, Francisco Azuajeen Limba Engleză Paperback – 5 ian 2005
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.
Toate formatele și edițiile | Preț | Express |
---|---|---|
Paperback (1) | 620.61 lei 6-8 săpt. | |
SPRINGER NETHERLANDS – 5 ian 2005 | 620.61 lei 6-8 săpt. | |
Hardback (1) | 625.40 lei 6-8 săpt. | |
SPRINGER NETHERLANDS – 7 feb 2005 | 625.40 lei 6-8 săpt. |
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Specificații
ISBN-13: 9781402029592
ISBN-10: 1402029594
Pagini: 240
Ilustrații: XVII, 221 p.
Dimensiuni: 170 x 244 x 13 mm
Greutate: 0.38 kg
Ediția:2004
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Computational Biology
Locul publicării:Dordrecht, Netherlands
ISBN-10: 1402029594
Pagini: 240
Ilustrații: XVII, 221 p.
Dimensiuni: 170 x 244 x 13 mm
Greutate: 0.38 kg
Ediția:2004
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Computational Biology
Locul publicării:Dordrecht, Netherlands
Public țintă
ResearchCuprins
Lazy Learning for Predictive Toxicology based on a Chemical Ontology.- QSAR Modeling of Mutagenicity on Non-Congeneric Sets of Organic Compounds.- Characterizing Gene Expression Time Series using a Hidden Markov Model.- Analysis of Large-Scale mRNA Expression Data Sets by Genetic Algorithms.- A Data-Driven, Flexible Machine Learning Strategy for the Classification of Biomedical Data.- Cooperative Metaheuristics for Exploring Proteomic Data.- Integrating Gene Expression Data, Protein Interaction Data, and Ontology-Based Literature Searches.- Ontologies in Bioinformatics and Systems Biology.- Natural Language Processing and Systems Biology.- Systems Level Modeling of Gene Regulatory Networks.- Computational Neuroscience for Cognitive Brain Functions.