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Lipid Droplet‐Localized Spindle Apparatus Coiled‐Coil Protein 1 Regulates Lipid Droplet Distribution
Advanced Science, EarlyView.SPDL1‐L, a long isoform of SPDL1, is identified as a bona fide lipid droplet‐associated protein that acts as a dynein adaptor to drive perinuclear clustering of lipid droplets. By linking lipid droplets to the microtubule network, SPDL1‐L extends the function of SPDL1 beyond mitosis and contributes to lipid droplet organization and nuclear remodeling ...
Honggang Su +10 more
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Partial least median of squares regression
Journal of Chemometrics, 2022Abstract In modern data analysis, there is an increasing availability of datasets with numerous variables. Linear models that deal with abundant predictor variables often have poor performance because they tend to produce large variances. As well known, partial least squares (PLS) regression standouts because it is serviceable even if
Zhonghao Xie +3 more
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Partial Least Squares Methods: Partial Least Squares Correlation and Partial Least Square Regression
2012Partial least square (PLS) methods (also sometimes called projection to latent structures) relate the information present in two data tables that collect measurements on the same set of observations. PLS methods proceed by deriving latent variables which are (optimal) linear combinations of the variables of a data table.
Hervé, Abdi, Lynne J, Williams
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Domain-Invariant Partial-Least-Squares Regression
Analytical Chemistry, 2018Multivariate calibration models often fail to extrapolate beyond the calibration samples because of changes associated with the instrumental response, environmental condition, or sample matrix. Most of the current methods used to adapt a source calibration model to a target domain exclusively apply to calibration transfer between similar analytical ...
Ramin Nikzad-Langerodi +3 more
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Partial Least‐Squares Regression
2013This chapter presents the most widely applied and, probably, satisfactory multivariate regression method used nowadays: partial least squares (PLS). Graphical explanations of many concepts are given to complement the more formal mathematical background. Several approaches to solving current problems are suggested.
José Manuel Andrade‐Garda +3 more
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Kernel Partial Least-Squares Regression
The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006A couple of regularized least squares regression models in a feature space are extended by the kernel partial least squares (KPLS) regression model in this paper. PLS is a method based on the projection of input (explanatory) variables to the latent variables (components), and has been developed and established as one of the multivariate statistical ...
null Bai Yifeng +2 more
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Domain adaptive partial least squares regression
Chemometrics and Intelligent Laboratory Systems, 2020Abstract In practical applications, the problem of training- and test-samples from different distributions is often encountered, such as instruments or external environmental factors change when measuring the data. Therefore, a multivariate calibration model established, based on the training set needs to be adaptive to meet the requirements of test ...
Guangzao Huang +5 more
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