Advances in single-cell transcriptomics enable measuring the gene expression of individual cells, allowing cells to be ordered by their state in a dynamic biological process. Many algorithms assign 'pseudotimes' to each cell, representing the progress along the biological process. Ordering the expression data according to such pseudotimes can be valuable for understanding the underlying regulator-gene interactions in a biological process, such as differentiation. However, the distribution of cells sampled along a transitional process, and hence that of the pseudotimes assigned to them, is not uniform. This prevents using many standard mathematical methods for analyzing the ordered gene expression states. We present Single-Cell Inference of Networks using Granger Ensembles (SCINGE), an algorithm for gene regulatory network inference from single-cell gene expression data. Given ordered singlecell data, SCINGE uses kernel-based Granger Causality regression, which smooths the irregular pseudotimes and missing expression values. It then aggregates the predictions from an ensemble of regression analyses with a modified Borda method to compile a ranked list of candidate interactions between transcriptional regulators and their target genes. In two mouse embryonic stem cell differentiation case studies, SCINGE outperforms other contemporary algorithms for gene network reconstruction. However, a more detailed examination reveals caveats about transcriptional network reconstruction with single-cell RNA-seq data. Network inference methods, including SCINGE, may have near random performance for predicting the targets of many individual regulators even if the aggregate performance is good. In

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The near zero temperature coefficient of resistivity (NZ-TCR) in Mn-based antiperovskite Mn3Ni1−xCuxN is reported. The temperature range of NZ-TCR is controllable by changing Cu content. Further, the TCR value of 0.09 ppm K−1 was obtained in Mn3Ni0.5Cu0.5N over a broad temperature range around room temperature. The anomalous resistivity change of Mn3Ni1−xCuxN from metal-like to NZ-TCR behavioris apparently due to a magnetic transition. The possible reason for the formation of NZ-TCR is interpreted on the basis of spin-disorder scattering.