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Titlebook: Statistical Analysis in Proteomics; Klaus Jung Book 2016 Springer Science+Business Media New York 2016 Data analysis.High-throughput data.

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發(fā)表于 2025-3-21 19:09:20 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Statistical Analysis in Proteomics
編輯Klaus Jung
視頻videohttp://file.papertrans.cn/877/876324/876324.mp4
概述Includes cutting-edge methods for the study of the statistical analysis of proteomics.Provides step-by-step detail essential for reproducible results.Contains key notes and implementation advice from
叢書名稱Methods in Molecular Biology
圖書封面Titlebook: Statistical Analysis in Proteomics; Klaus Jung Book 2016 Springer Science+Business Media New York 2016 Data analysis.High-throughput data.
描述.This valuable collection aims to provide a collection of frequently used statistical methods in the field of proteomics. Although there is a large overlap between statistical methods for the different ‘omics’ fields, methods for analyzing data from proteomics experiments need their own specific adaptations. To satisfy that need, .Statistical Analysis in Proteomics. focuses on the planning of proteomics experiments, the preprocessing and analysis of the data, the integration of proteomics data with other high-throughput data, as well as some special topics. Written for the highly successful .Methods in Molecular Biology. series, the chapters contain the kind of detail and expert implementation advice that makes for a smooth transition to the laboratory..Practical and authoritative, .Statistical Analysis in Proteomics. serves as an ideal reference for statisticians involved in the planning and analysis of proteomics experiments, beginners as well as advanced researchers, and also for biologists, biochemists, and medical researchers who want to learn more about the statistical opportunities in the analysis of proteomics data..
出版日期Book 2016
關(guān)鍵詞Data analysis; High-throughput data; Omics; Preprocessing; Statistical methods
版次1
doihttps://doi.org/10.1007/978-1-4939-3106-4
isbn_softcover978-1-4939-7987-5
isbn_ebook978-1-4939-3106-4Series ISSN 1064-3745 Series E-ISSN 1940-6029
issn_series 1064-3745
copyrightSpringer Science+Business Media New York 2016
The information of publication is updating

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Methods in Molecular Biologyhttp://image.papertrans.cn/s/image/876324.jpg
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Visualization and Differential Analysis of Protein Expression Data Using RData analysis is essential to derive meaningful conclusions from proteomic data. This chapter describes ways of performing common data visualization and differential analysis tasks on gel-based proteomic datasets using a freely available statistical software package (R). A workflow followed is illustrated using a synthetic dataset as example.
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發(fā)表于 2025-3-22 15:45:45 | 只看該作者
Klaus JungIncludes cutting-edge methods for the study of the statistical analysis of proteomics.Provides step-by-step detail essential for reproducible results.Contains key notes and implementation advice from
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Tsung-Heng Tsai,Minkun Wang,Habtom W. Ressomve numerical and spice level simulations.Well balanced topic.Semiconductor power electronics plays a dominant role due its increased efficiency and high reliability in various domains including the medium and high electrical drives, automotive and aircraft applications, electrical power conversion,
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發(fā)表于 2025-3-23 01:25:33 | 只看該作者
Antonella Chiechive numerical and spice level simulations.Well balanced topic.Semiconductor power electronics plays a dominant role due its increased efficiency and high reliability in various domains including the medium and high electrical drives, automotive and aircraft applications, electrical power conversion,
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