Artificial Intelligence Methods and Tools for Systems Biology:
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 an...
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Dordrecht
Springer Netherlands
2004
|
| Ausgabe: | 1st ed. 2004 |
| Schriftenreihe: | Computational Biology
5 |
| Schlagworte: | |
| Online-Zugang: | UBY01 Volltext |
| Zusammenfassung: | 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 |
| Beschreibung: | 1 Online-Ressource (XVII, 221 p) |
| ISBN: | 9781402028656 |
| DOI: | 10.1007/978-1-4020-5811-0 |
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| edition | 1st ed. 2004 |
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| index_date | 2024-07-03T16:12:21Z |
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| isbn | 9781402028656 |
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| spelling | Artificial Intelligence Methods and Tools for Systems Biology edited by W. Dubitzky, Francisco Azuaje 1st ed. 2004 Dordrecht Springer Netherlands 2004 1 Online-Ressource (XVII, 221 p) txt rdacontent c rdamedia cr rdacarrier Computational Biology 5 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 Life Sciences, general Artificial Intelligence Computer Science, general Evolutionary Biology Life sciences Artificial intelligence Computer science Evolutionary biology Dubitzky, W. edt Azuaje, Francisco edt Erscheint auch als Druck-Ausgabe 9781402028595 Erscheint auch als Druck-Ausgabe 9781402029592 Erscheint auch als Druck-Ausgabe 9789401571081 https://doi.org/10.1007/978-1-4020-5811-0 Verlag URL des Eerstveröffentlichers Volltext |
| spellingShingle | Artificial Intelligence Methods and Tools for Systems Biology Life Sciences, general Artificial Intelligence Computer Science, general Evolutionary Biology Life sciences Artificial intelligence Computer science Evolutionary biology |
| title | Artificial Intelligence Methods and Tools for Systems Biology |
| title_auth | Artificial Intelligence Methods and Tools for Systems Biology |
| title_exact_search | Artificial Intelligence Methods and Tools for Systems Biology |
| title_exact_search_txtP | Artificial Intelligence Methods and Tools for Systems Biology |
| title_full | Artificial Intelligence Methods and Tools for Systems Biology edited by W. Dubitzky, Francisco Azuaje |
| title_fullStr | Artificial Intelligence Methods and Tools for Systems Biology edited by W. Dubitzky, Francisco Azuaje |
| title_full_unstemmed | Artificial Intelligence Methods and Tools for Systems Biology edited by W. Dubitzky, Francisco Azuaje |
| title_short | Artificial Intelligence Methods and Tools for Systems Biology |
| title_sort | artificial intelligence methods and tools for systems biology |
| topic | Life Sciences, general Artificial Intelligence Computer Science, general Evolutionary Biology Life sciences Artificial intelligence Computer science Evolutionary biology |
| topic_facet | Life Sciences, general Artificial Intelligence Computer Science, general Evolutionary Biology Life sciences Artificial intelligence Computer science Evolutionary biology |
| url | https://doi.org/10.1007/978-1-4020-5811-0 |
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