Single cell proteomics in biomedicine: High-dimensional data acquisition, visualization, and analysis.


:New insights on cellular heterogeneity in the last decade provoke the development of a variety of single cell omics tools at a lightning pace. The resultant high-dimensional single cell data generated by these tools require new theoretical approaches and analytical algorithms for effective visualization and interpretation. In this review, we briefly survey the state-of-the-art single cell proteomic tools with a particular focus on data acquisition and quantification, followed by an elaboration of a number of statistical and computational approaches developed to date for dissecting the high-dimensional single cell data. The underlying assumptions, unique features, and limitations of the analytical methods with the designated biological questions they seek to answer will be discussed. Particular attention will be given to those information theoretical approaches that are anchored in a set of first principles of physics and can yield detailed (and often surprising) predictions.






Su Y,Shi Q,Wei W




Has Abstract


2017-02-01 00:00:00










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    pub_type: 杂志文章


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    pub_type: 杂志文章


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    pub_type: 评论,杂志文章


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    authors: Wang Y,Xu LY,Lam KS,Lu G,Cooper GJ,Xu A

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    pub_type: 杂志文章,评审


    authors: Hajduch M,Matusova R,Houston NL,Thelen JJ

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    authors: White MY,Tchen AS,McCarron HC,Hambly BD,Jeremy RW,Cordwell SJ

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    pub_type: 杂志文章


    authors: Castagna A,Antonioli P,Astner H,Hamdan M,Righetti SC,Perego P,Zunino F,Righetti PG

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    pub_type: 杂志文章


    authors: Chen CH,Zhang XQ,Lo CW,Liu PF,Liu YT,Gallo RL,Hsieh MF,Schooley RT,Huang CM

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    pub_type: 杂志文章


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    更新日期:2004-03-01 00:00:00

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    pub_type: 杂志文章


    authors: Ritz D,Gloger A,Weide B,Garbe C,Neri D,Fugmann T

    更新日期:2016-05-01 00:00:00