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Computational methods for single-cell data analysis
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Year: [2019]
Publisher: New York, NY, Humana Press, Springer Science+Business Media, LLC, part of Springer Nature
Media group: Ausleihbestand
availableavailable
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BranchLocationsStatusReservationsDue dateBarcodeFloor planLending note
Branch: Hauptstelle Locations: ZB-130 129 / Ausstellungsregal Status: available Reservations: 0 Due date: Barcode: 00304999 Floor plans: Floor plan Lending note:
Content
This detailed book provides state-of-art computational approaches to further explore the exciting opportunities presented by single-cell technologies. Chapters each detail a computational toolbox aimed to overcome a specific challenge in single-cell analysis, such as data normalization, rare cell-type identification, and spatial transcriptomics analysis, all with a focus on hands-on implementation of computational methods for analyzing experimental data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.
 
Authoritative and cutting-edge, Computational Methods for Single-Cell Data Analysis aims to cover a wide range of tasks and serves as a vital handbook for single-cell data analysis.
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Details
Statement of Responsibility: edited by Guo-Cheng Yuan, Dana-Farber Cancer Institute and Harvard Chan School of Public Health, Boston, MA, USA
Year: [2019]
Publisher: New York, NY, Humana Press, Springer Science+Business Media, LLC, part of Springer Nature
Classification: ZB-130, MA-20
ISBN: 9781493990566
ISBN (2nd): 149399056X
Description: x, 271 Seiten, Diagramme, Illustrationen
Tags: Datenverarbeitung, Zellbiologie Methoden
Participating parties: Yuan, Guo-Cheng
Language: Englisch
Original title: Computational methods for single-cell data analysis
Media group: Ausleihbestand

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