标题 输出 CanvasXpress R库 html_document 独立的 canvasXpress是百时美施贵宝公司开发的用于生物信息学和系统生物学分析的核心可视化组件。 它支持大量的以显示科学和非科学数据。 canvasXpress还包括用于浏览复杂数据集的简单,简洁的,用于跟踪可目的的所有用户自定义的复杂而独特的机制,以及用于同步选定数据点的“开箱即用”广播功能。页面中的所有canvasXpress图。 可以轻松地对数据进行排序,分组,转置,转换或动态聚类。 完全可定制的鼠标事件以及缩放,平移和拖放功能是使此库在其类中独一无二的功能。 现在, canvasXpress可以简单地
2021-02-06 09:04:47 1.75MB visualization javascript chart bioinformatics
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SCDE概述 scde程序包实现了一组用于分析单细胞RNA-seq数据的统计方法。 scde适合用于单细胞RNA-seq测量的单个误差模型。 然后可以将这些模型用于评估细胞组之间的差异表达以及其他类型的分析。 scde软件包还包含pagoda框架,该pagoda框架应用途径和基因集过度分散分析来识别单细胞之间转录异质性的各个方面。 以下出版物详细介绍了差异表达分析的总体方法: 在以下出版物中详细介绍了途径和基因组过度分散分析的总体方法: 有关其他安装信息,教程等,请访问 样品分析和图像 单细胞错误建模 scde使用源自单细胞RNA-seq数据的计数scde拟合单细胞的个体误差模型,
2021-02-05 15:10:22 3.93MB bioinformatics r analysis ngs
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Python course in Bioinformatics.pdf
2021-01-28 02:26:07 1.33MB python
Beginning Perl for Bioinformatics_HTML版.rar Beginning Perl for Bioinformatics_HTML版.rar
2021-01-28 02:23:54 773KB Beginning Perl for Bioinformatics
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Contents 1 ThisDocument 1 2 BioperlBasics 1 2.1 BioperlSemantics .......................................... 1 2.1.1 BioperlNamespace..................................... 1 2.1.2 Interfaces........................................... 1 3 SequenceAnalysis 2 3.1 SequenceObjects..........................
2021-01-28 02:23:53 108KB Using bioperl for bioinformatics
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Bioinformatics with R Cookbook. 包括如何用R分析microarray, RNA-seq,GWAS, NGS 数据, 分析蛋白质和核酸序列等等
2020-03-25 03:14:55 28.35MB 生物信息
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生物信息学算法导论,英文原版 an-introduction-to-bioinformatics-algorithms,有需要的可以下载
2020-01-15 03:05:41 3.18MB an-introduct
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Bioinformatics_Algorithms_-_Design_and_Implementation_in_Python.pdf
2020-01-06 03:12:28 6.99MB 综合文档
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生物信息学的圣经,作为教程值得一度 Suitable for advanced undergraduates and postgraduates, Understanding Bioinformatics provides a definitive guide to this vibrant and evolving discipline. The book takes a conceptual approach. It guides the reader from first principles through to an understanding of the computational techniques and the key algorithms. Understanding Bioinformatics is an invaluable companion for students from their first encounter with the subject through to more advanced studies. The book is divided into seven parts, with the opening part introducing the basics of nucleic acids, proteins and databases. Subsequent parts are divided into 'Applications' and 'Theory' Chapters, allowing readers to focus their attention effectively. In each section, the Applications Chapter provides a fast and straightforward route to understanding the main concepts and 'getting started'. Each of these is then followed by Theory Chapters which give greater detail and present the underlying mathematics. In Part 2, Sequence Alignments, the Applications Chapter shows the reader how to get started on producing and analyzing sequence alignments, and using sequences for database searching, while the next two chapters look closely at the more advanced techniques and the mathematical algorithms involved. Part 3 covers evolutionary processes and shows how bioinformatics can be used to help build phylogenetic trees. Part 4 looks at the characteristics of whole genomes. In Parts 5 and 6 the focus turns to secondary and tertiary structure – predicting structural conformation and analysing structure-function relationships. The last part surveys methods of analyzing data from a set of genes or proteins of an organism and is rounded off with an overview of systems biology. The writing style of Understanding Bioinformatics is notable for its clarity, while the extensive, full-color artwork has been designed to present the key concepts with simplicity and consistency. Each chapter uses mind-maps and fl
2020-01-04 03:15:24 41.29MB 生物信息学
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Bioinformatics生物信息学:序列和基因组分析.pdf 英文版
2019-12-21 20:34:42 7.43MB 生物信息学 序列 基因组分析
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