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SC3 - consensus clustering of single-cell RNA-Seq data
TLDR
It is demonstrated that SC3 is capable of identifying subclones from the transcriptomes of neoplastic cells collected from patients and achieves high accuracy and robustness by combining multiple clustering solutions through a consensus approach.
Synchronization in small-world systems.
TLDR
Applied to networks of low redundancy, the small-world route produces synchronizability more efficiently than standard deterministic graphs, purely random graphs, and ideal constructive schemes.
Transcriptome-wide noise controls lineage choice in mammalian progenitor cells
TLDR
Clonal heterogeneity of gene expression level is not due to independent noise in the expression of individual genes, but reflects metastable states of a slowly fluctuating transcriptome that is distinct in individual cells and may govern the reversible, stochastic priming of multipotent progenitor cells in cell fate decision.
Laplacian Dynamics and Multiscale Modular Structure in Networks
Most methods proposed to uncover communities in complex networks rely on their structural properties. Here we introduce the stability of a network partition, a measure of its quality defined in terms
Stability of graph communities across time scales
TLDR
The stability of a partition is introduced, a measure of its quality as a community structure based on the clustered autocovariance of a dynamic Markov process taking place on the network, and the dynamical definition provides a unifying framework for several standard partitioning measures.
PDGFRα demarcates the cardiogenic clonogenic Sca1+ stem/progenitor cell in adult murine myocardium
TLDR
PDGFRα demarcates the clonogenic cardiogenic Sca1+ stem/progenitor cell, and four subpopulations of cardiac progenitor/stem cells in adult mouse myocardium all sharing stem cell antigen-1 (Sca1), based on side population (SP) phenotype, PECAM-1 and platelet-derived growth factor receptor-α (PDG FRα) expression are defined.
Titration of chaos with added noise
TLDR
It is shown that the controlled addition of white or colored noise to a signal with a preexisting noise floor results in a titration index that faithfully tracks the onset of deterministic chaos in all standard bifurcation routes to chaos and gives a relative measure of chaos intensity.
Detection of nonlinear dynamics in short, noisy time series
TLDR
A computational procedure is presented, based on a comparison of the prediction power of linear and nonlinear models of the Volterra–Wiener form, which is capable of robust and highly sensitive statistical detection of deterministic dynamics, including chaotic dynamics, in experimental time series.
Random Walks, Markov Processes and the Multiscale Modular Organization of Complex Networks
TLDR
This dynamic framework creates a systematic link between different stochastic dynamics and their corresponding notions of optimal communities under distinct (node and edge) centralities and shows that the Markov Stability can be computed efficiently to find multi-scale community structure in large networks.
Natural Connectivity of Complex Networks
TLDR
It is shown that the natural connectivity can be derived mathematically from the graph spectrum as an average eigenvalue and that it changes strictly monotonically with the addition or deletion of edges.
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