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Microarray Quality Control

Autor Wei Zhang, Ilya Shmulevich, Jaakko Astola
en Limba Engleză Hardback – 4 mar 2004
Microarray technology provides researchers in the life sciences with a revolutionary tool for measuring gene expression. However, this highly developed process involves multiple steps, from sample selection to data analysis, each susceptible to potentially costly errors. Without sound quality control, experimental microarrays may produce useless or, even worse, misleading results. Microarray Quality Control provides a comprehensive resource for ensuring quality control in every step of this complex process. From experimental design to data processing, analysis, and interpretation, the emphasis in this text remains on practical advice for each stage of planning and running a microarray study. Chapters cover: * Quality of biological samples * Quality of DNA * Hybridization protocols Scanning * Data acquisition * Image analysis * Data analysis Written for the broad group of workers-biologists, mathematicians, statisticians, engineers, physicians, and computational scientists-involved in microarray studies, Microarray Quality Control features a straightforward style easily accessed by various disciplines. Useful checklists and tips help ensure the integrity of results, and each chapter contains a thorough review of pertinent literature. The only complete, systematic treatment of the topic available, Microarray Quality Control offers students and practitioners an invaluable resource for improving experimental quality and efficiency.
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Specificații

ISBN-13: 9780471453444
ISBN-10: 0471453447
Pagini: 168
Dimensiuni: 161 x 242 x 17 mm
Greutate: 0.41 kg
Ediția:New.
Editura: Wiley
Locul publicării:Hoboken, United States

Public țintă

Biomedical researchers working with microarrays, biotechnologists, computational biologists, biological mathematicians, biomedical engineers and biostatisticians.

Descriere

Microarray technology provides researchers in the life sciences with a revolutionary tool for measuring gene expression. However, this highly developed process involves multiple steps, from sample selection to data analysis, each susceptible to potentially costly errors.