Verwandte Artikel zu A Practical Approach to Microarray Data Analysis
Inhaltsangabe
In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Reseña del editor
In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.
Reseña del editor
The book addresses the requirement of scientists and researchers to gain a basic understanding of microarray analysis methodologies and tools. It is intended for students, teachers, researchers, and research managers who want to understand the state of the art and of the presented methodologies and the areas in which gaps in our knowledge demand further research and development. The book is designed to be used by the practicing professional tasked with the design and analysis of microarray experiments or as a text for a senior undergraduate- or graduate level course in analytical genetics, biology, bioinformatics, computational biology, statistics and data mining, or applied computer science.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
- VerlagSpringer
- Erscheinungsdatum2002
- ISBN 10 1402072600
- ISBN 13 9781402072604
- EinbandTapa dura
- SpracheEnglisch
- Anzahl der Seiten388
- HerausgeberBerrar Daniel P., Dubitzky Werner, Granzow Martin
- Kontakt zum HerstellerNicht verfügbar
EUR 10,18
EUR 5,87 für den Versand von Vereinigtes Königreich nach Deutschland
Versandziele, Kosten & DauerNeu kaufen
Diesen Artikel anzeigen
EUR 48,37
Gratis für den Versand innerhalb von/der Deutschland
Versandziele, Kosten & DauerWeitere beliebte Ausgaben desselben Titels
Suchergebnisse für A Practical Approach to Microarray Data Analysis
Beispielbild für diese ISBN
A Practical Approach to Microarray Data Analysis
Anbieter: Better World Books Ltd, Dunfermline, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
Zustand: Good. Ships from the UK. Former library book; may include library markings. Used book that is in clean, average condition without any missing pages. Bestandsnummer des Verkäufers 2642910-20
Anzahl: 1 verfügbar
Beispielbild für diese ISBN
A Practical Approach to Microarray Data Analysis
Anbieter: Better World Books, Mishawaka, IN, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: Very Good. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects. Bestandsnummer des Verkäufers 15430058-6
Anzahl: 1 verfügbar
Foto des Verkäufers
A Practical Approach to Microarray Data Analysis
Print-on-DemandAnbieter: moluna, Greven, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Gebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Addresses the requirement of scientists and researchers to gain a basic understanding of microarray analysis methodologies and toolsIn the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community a. Bestandsnummer des Verkäufers 4094953
Anzahl: Mehr als 20 verfügbar
Foto des Verkäufers
A Practical Approach to Microarray Data Analysis
Print-on-DemandAnbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships. 384 pp. Englisch. Bestandsnummer des Verkäufers 9781402072604
Anzahl: 2 verfügbar
Foto des Verkäufers
A Practical Approach to Microarray Data Analysis
Verlag:
Springer US, Springer US Dez 2002, 2002
ISBN 10: 1402072600
ISBN 13: 9781402072604
Neu
Hardcover
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Buch. Zustand: Neu. Neuware -In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 384 pp. Englisch. Bestandsnummer des Verkäufers 9781402072604
Anzahl: 2 verfügbar
Foto des Verkäufers
A Practical Approach to Microarray Data Analysis
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships. Bestandsnummer des Verkäufers 9781402072604
Anzahl: 1 verfügbar
Beispielbild für diese ISBN
A Practical Approach to Microarray Data Analysis
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
Zustand: New. In. Bestandsnummer des Verkäufers ria9781402072604_new
Anzahl: Mehr als 20 verfügbar
Beispielbild für diese ISBN
A Practical Approach to Microarray Data Analysis
Verlag:
Springer-Verlag New York Inc., 2002
ISBN 10: 1402072600
ISBN 13: 9781402072604
Neu
Hardcover
Anbieter: THE SAINT BOOKSTORE, Southport, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
Hardback. Zustand: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 749. Bestandsnummer des Verkäufers C9781402072604
Anzahl: Mehr als 20 verfügbar
Beispielbild für diese ISBN
A Practical Approach To Microarray Data Analysis
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide. Bestandsnummer des Verkäufers ABNR-81848
Anzahl: 1 verfügbar
Beispielbild für diese ISBN
A Practical Approach To Microarray Data Analysis
Anbieter: Basi6 International, Irving, TX, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Bestandsnummer des Verkäufers ABEJUNE24-167654
Anzahl: 1 verfügbar