This valuable study introduces a non-perturbative pulse-labeling strategy for yeast nuclear pore complexes (NPCs), employing a nanobody-based approach in order to selectively capture Nup84-containing ...

Non-linearity A relationship between two variables is non-linear if every unit change in the independent continuous variable does not lead to a constant proportional change in the dependent variable.

We consider two further factors in the study: discriminability level for each visual variable as a factor intrinsic to the visual variables and graph-task type (visual search versus comparison) as a ...

The Independent has announced two new launches at Advertising Week Europe: Independent Studio and Bulletin. Left to right: Christian Broughton, Chloe Hubbard, Zoe Kalar, Adam Clery. Photograph: ...

G. Bennett, Upper Bounds on the Moments and Probability Inequalities for the Sum of Independent, Bounded Random Variables, Biometrika, Vol. 52, No. 3/4 (Dec., 1965), pp. 559-569 ...

Enhanced sampling simulations make the computational study of rare events feasible. A large family of such methods crucially depends on the definition of some collective variables (CVs) that could ...

How to Make a Graph in Excel With Word and Number Variables. Microsoft Excel can perform numerous statistical functions, as well as create charts from statistical data. Statistical data includes ...

How to Run a Multivariate Regression in Excel. Multivariate regression enables you to relate one dependent variable to multiple independent variables you've derived from surveys or measurements.

We study a graph-constrained regularization procedure and its theoretical properties for regression analysis to take into account the neighborhood information of the variables measured on a graph.

The relation can be described algebraically by a two variable function or equation. But it is often useful to represent the relation in a two-dimensional graph. Such a graph is known as a scatter ...

In this study, we present a graph neural network (GNN)-based learning approach using an autoencoder setup to derive low-dimensional variables from features observed in experimental crystal structures.