Titlebook: Computational Stem Cell Biology; Methods and Protocol Patrick Cahan Book 2019 Springer Science+Business Media, LLC, part of Springer Nature

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书目名称Computational Stem Cell Biology影响因子(影响力)




书目名称Computational Stem Cell Biology影响因子(影响力)学科排名




书目名称Computational Stem Cell Biology网络公开度




书目名称Computational Stem Cell Biology网络公开度学科排名




书目名称Computational Stem Cell Biology被引频次




书目名称Computational Stem Cell Biology被引频次学科排名




书目名称Computational Stem Cell Biology年度引用




书目名称Computational Stem Cell Biology年度引用学科排名




书目名称Computational Stem Cell Biology读者反馈




书目名称Computational Stem Cell Biology读者反馈学科排名

magnate

Tailor

Sustainable Tertiary Education in Asialusters of densely connected cells. This subpopulation structure represents a map of putative cell-state transitions. CellRouter implements a flow network algorithm to explore this map and reconstruct cell-state transitions in complex single-cell, multidimensional omics datasets. We describe a step-

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André Matthes,Katja Beyer,Anton Schumannl biologists. We focus specifically on the use of one tool, called Iterative Clustering and Guide-gene Selection (ICGS), which has been shown to uncover novel committed, transitional, and metastable progenitor cell states. As a component of the AltAnalyze toolkit, ICGS provides advanced methods to e

有毛就脱毛

Modeling Cellular Differentiation and Reprogramming with Gene Regulatory Networks GRN can enable control of the eventual cell fates with potential clinical applications. In this chapter, we describe our computational methodologies that we have tailor-made with purpose of applications to cell fate control. Briefly, we introduce the process of cellular differentiation and reprogra

规章

Computational Tools for Quantifying Concordance in Single-Cell Fateifetime and to model the deterministic effect of cell environment and inheritance, i.e., nature versus nurture. We have applied competing risks statistics, a branch of survival statistics, to quantify cell fate concordance from cell lifetime data. Competing risks modelling of cell fate concordance p

规章

碎石头

Investigating Cell Fate Decisions with ICGS Analysis of Single Cellsl biologists. We focus specifically on the use of one tool, called Iterative Clustering and Guide-gene Selection (ICGS), which has been shown to uncover novel committed, transitional, and metastable progenitor cell states. As a component of the AltAnalyze toolkit, ICGS provides advanced methods to e

法官

背心

https://doi.org/10.1007/978-1-4939-9224-9gene regulatory networks; single-cell transcriptome data; teratomas; engineered cells; fetal tissues