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Software Tools and Algorithms for Biological Systems
Details
Software Tools and Algorithms for Biological Systems" is composed of a collection of papers received in response to an announcement that was widely distributed to academicians and practitioners in the broad area of computational biology and software tools. Also, selected authors of accepted papers of BIOCOMP'09 proceedings (International Conference on Bioinformatics and Computational Biology: July 13-16, 2009; Las Vegas, Nevada, USA) were invited to submit the extended versions of their papers for evaluation.
All aspects of software tools and algorithms as they relate to biological systems will be covered in this book This book looks at the major progress that has been made in a wide range of topics that fall under the field of biological systems Important topics in the area of computer-based medical systems appear are examined Includes supplementary material: sn.pub/extras
Inhalt
Preface.- Computational Methods for Microarray, Gene Expression Analysis, and Gene Regulatory Networks.- Bioinformatics Databases, Data Mining, and Pattern Discovery Techniques.- Protein Classification & Structure Prediction, and Computational Structural Biology.- Comparative Sequence, Genome Analysis, Genome Assembly, and Genome Scale Computational Methods.- Experimental Medicine and Analysis Tools.- Computational Methods for Filtering, Noise Cancellation, and Signal & Image Processing.- Computer-Based Medical Systems.- Software Packages and Other Computational Topics in Bioinformatics.- Index.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09781441970459
- Editor Hamid Arabnia, Quoc-Nam Tran
- Sprache Englisch
- Auflage 2011 edition
- Größe H245mm x B169mm x T47mm
- Jahr 2011
- EAN 9781441970459
- Format Fester Einband
- ISBN 978-1-4419-7045-9
- Veröffentlichung 06.04.2011
- Titel Software Tools and Algorithms for Biological Systems
- Untertitel Advances in Experimental Medicine and Biology 696
- Gewicht 1349g
- Herausgeber Springer-Verlag GmbH
- Anzahl Seiten 776
- Lesemotiv Verstehen
- Genre Biologie