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A Branch Point on Differentiation Trajectory is the Bifurcating Event Revealed by Dynamical Network Biomarker Analysis of Single-Cell Data
Chen, Ziwei1,2; Bai, Xiangqi1,2; Ma, Liang2,3; Wang, Xiawei4; Liu, Xiuqin5; Liu, Yuting6; Chen, Luonan7,8; Wan, Lin1,2
2020-03-01
发表期刊IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
ISSN1545-5963
卷号17期号:2页码:366-375
摘要The advance in single-cell profiling technologies and the development in computational algorithms provide the opportunity to reconstruct pseudo temporal trajectory with branch point of cellular development. On the other hand, theories such as dynamical network biomarkers (DNB) theory have been recently proposed to characterize the pre-transition state in biological systems. Few studies have validated whether the branch point identified in pseudo time is the critical point in dynamical system. In this study, the dynamical behavior of the branch point on the pseudo trajectory has been investigated. We study the pseudo temporal trajectories reconstructed by Wishbone and diffusion pseudotime analysis (DPT) algorithms, as well as the simulated trajectory. DNB theory is applied to justify the bifurcating event on the pseudo trajectories. Our results demonstrate that the branch point recovered by Wishbone and DPT algorithms is confirmed as a transition state in cell differentiation process by DNB theory. Furthermore, we show that an appropriate DNB group will amplify the comprehensive index of critical event as defined in DNB theory. Our study provides biological insights on pseudo trajectory with branch point in a dynamical view and also indicates that DNB theory may serve as a benchmark to check the validity of branch point.
关键词Trajectory Heuristic algorithms Mice Correlation Reactive power Pseudo temporal trajectory branch point DNB theory reconstruction single-cell data bifurcation dynamical system
DOI10.1109/TCBB.2018.2847690
收录类别SCI
语种英语
资助项目Strategic Priority Research Program of the CAS[XDB13050000] ; NSFC[11571349] ; NSFC[31771476] ; NSFC[91529303] ; NSFC[91530105] ; NSFC[91630314] ; NSFC[81673833] ; NCMIS of the CAS ; Youth Innovation Promotion Association of the CAS ; Key Laboratory of Systems and Control of the CAS ; NSF[DMS 1440386]
WOS研究方向Biochemistry & Molecular Biology ; Computer Science ; Mathematics
WOS类目Biochemical Research Methods ; Computer Science, Interdisciplinary Applications ; Mathematics, Interdisciplinary Applications ; Statistics & Probability
WOS记录号WOS:000524236800001
出版者IEEE COMPUTER SOC
引用统计
文献类型期刊论文
条目标识符http://ir.amss.ac.cn/handle/2S8OKBNM/51134
专题中国科学院数学与系统科学研究院
通讯作者Ma, Liang; Chen, Luonan; Wan, Lin
作者单位1.Chinese Acad Sci, Acad Math & Syst Sci, LSC, NCMIS, Beijing 100864, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Beijing Inst Genom, Beijing 100101, Peoples R China
4.Univ Wisconsin, Dept Stat, Madison, WI 53706 USA
5.Univ Sci & Technol Beijing, Sch Math & Phys, Beijing 100083, Peoples R China
6.Beijing Jiaotong Univ, Sch Sci, Beijing 100044, Peoples R China
7.Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Biochem & Cell Biol, Key Lab Syst Biol,CAS Ctr Excellence Mol Cell Sci, Shanghai 200031, Peoples R China
8.Chinese Acad Sci, CAS Ctr Excellence Anim Evolut & Genet, Kunming 650223, Yunnan, Peoples R China
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Chen, Ziwei,Bai, Xiangqi,Ma, Liang,et al. A Branch Point on Differentiation Trajectory is the Bifurcating Event Revealed by Dynamical Network Biomarker Analysis of Single-Cell Data[J]. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS,2020,17(2):366-375.
APA Chen, Ziwei.,Bai, Xiangqi.,Ma, Liang.,Wang, Xiawei.,Liu, Xiuqin.,...&Wan, Lin.(2020).A Branch Point on Differentiation Trajectory is the Bifurcating Event Revealed by Dynamical Network Biomarker Analysis of Single-Cell Data.IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS,17(2),366-375.
MLA Chen, Ziwei,et al."A Branch Point on Differentiation Trajectory is the Bifurcating Event Revealed by Dynamical Network Biomarker Analysis of Single-Cell Data".IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 17.2(2020):366-375.
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