pls toolbox 5.0 for Search Results


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Umetrics pls regression analysis
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Umetrics loading plot of pls
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Sarstedt teste para avaliação de efeitos de moderação com variáveis categóricas em pls
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GL Sciences gl-pak pls-2 (pls-2) of the styrene divinyl benzene co-polymer column
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Chromogenix s2251
Robustness analyses. (A) A two-parameter bifurcation diagram with respect to parameters <t>k1</t> <t>(substrate</t> affinity) and keffPLS <t>(PLS</t> efficiency) depicts the area of bistability (i.e., the shaded portion inside the cusp). (B) Using parameter vectors generated with ±20% to ±50% random variation from the nominal parameters, the percent of models retaining bistability was calculated using keffPLS as the bifurcation parameter. (C) Percent bistability when each parameter is perturbed individually (see “Computational methods”).
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Umetrics pca and pls
<t>Multivariate</t> pairwise-analysis of patient groups. (a) <t>PLS-DA</t> comparison between the HCM and control groups using blood samples from all three sampling sites (CS, AR, FV) (R 2 X=36%, R 2 Y=41%, Q 2 =18%). (b) PLS-DA comparison between the AS and control groups using blood samples from all three sampling sites (CS, AR, FV) (R 2 X=38%, R 2 Y=64%, Q 2 =54%). (c) PLS-DA comparison between the HCM and AS groups using blood samples from all three sampling sites (CS, AR, FV) (R 2 X=44%, R 2 Y=70%, Q 2 =53%) (d) Random permutation test of the model validity for the model in b. (e) PLS-DA comparison between the control and AS groups using blood samples from the CS (R 2 X=30%, R 2 Y=59%, Q 2 =37%). (f) Box-whisker plots of key metabolites that are discriminatory between the AS and control groups for the model in e. (g) PLS-DA comparison between the HCM and AS groups using blood samples from the CS (R 2 X=29%, R 2 Y=47%; Q 2 =18%). (h) ROC analysis of the predictive capability of the model in e discriminating between AS and control groups.
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Umetrics simca-p 11.0
Predictor variables selected for multivariate orthogonal <t> partial least square </t> <t> (O-PLS) </t> regression model for cervical kinematics
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Image Search Results


Robustness analyses. (A) A two-parameter bifurcation diagram with respect to parameters k1 (substrate affinity) and keffPLS (PLS efficiency) depicts the area of bistability (i.e., the shaded portion inside the cusp). (B) Using parameter vectors generated with ±20% to ±50% random variation from the nominal parameters, the percent of models retaining bistability was calculated using keffPLS as the bifurcation parameter. (C) Percent bistability when each parameter is perturbed individually (see “Computational methods”).

Journal: Biophysical Journal

Article Title: Steady States and Dynamics of Urokinase-Mediated Plasmin Activation In Silico and In Vitro

doi: 10.1016/j.bpj.2011.08.054

Figure Lengend Snippet: Robustness analyses. (A) A two-parameter bifurcation diagram with respect to parameters k1 (substrate affinity) and keffPLS (PLS efficiency) depicts the area of bistability (i.e., the shaded portion inside the cusp). (B) Using parameter vectors generated with ±20% to ±50% random variation from the nominal parameters, the percent of models retaining bistability was calculated using keffPLS as the bifurcation parameter. (C) Percent bistability when each parameter is perturbed individually (see “Computational methods”).

Article Snippet: The chromogenic substrate of PLS, S2251 (0.4 mM), with chemical formula H-D-Val-Leu-Lys-pNA.2HCl, was purchased from Chromogenix (Milano, Italy).

Techniques: Generated

Model of UPA-mediated PLS activation. (A) The initiator precursor protease scUPA activates PLG to form PLS (arrow 1). PLS cleaves scUPA to produce the completely active tcUPA form (arrow 2), which can then provide feedback on PLG to make more PLS (arrow 3). Enzymatic reactions (dashed arrows) catalyze transitions (solid arrows) between substrate and product. (B) Convergence of PLS concentration over time, after the model is initialized with random concentrations of all the species. (C) A transition of the PLS steady state that is dependent on the initial concentration of scUPA. (D) “Going-up” (red line) and “coming-down” (blue line) simulations obtained using different values of keffPLS while measuring PLS steady-state levels. Arrows follow the transition of PLS concentrations from one steady state to another with changing parameter values. The simulations were done using the parameter values in Table 2 with ci = 2.

Journal: Biophysical Journal

Article Title: Steady States and Dynamics of Urokinase-Mediated Plasmin Activation In Silico and In Vitro

doi: 10.1016/j.bpj.2011.08.054

Figure Lengend Snippet: Model of UPA-mediated PLS activation. (A) The initiator precursor protease scUPA activates PLG to form PLS (arrow 1). PLS cleaves scUPA to produce the completely active tcUPA form (arrow 2), which can then provide feedback on PLG to make more PLS (arrow 3). Enzymatic reactions (dashed arrows) catalyze transitions (solid arrows) between substrate and product. (B) Convergence of PLS concentration over time, after the model is initialized with random concentrations of all the species. (C) A transition of the PLS steady state that is dependent on the initial concentration of scUPA. (D) “Going-up” (red line) and “coming-down” (blue line) simulations obtained using different values of keffPLS while measuring PLS steady-state levels. Arrows follow the transition of PLS concentrations from one steady state to another with changing parameter values. The simulations were done using the parameter values in Table 2 with ci = 2.

Article Snippet: The chromogenic substrate of PLS, S2251 (0.4 mM), with chemical formula H-D-Val-Leu-Lys-pNA.2HCl, was purchased from Chromogenix (Milano, Italy).

Techniques: Activation Assay, Concentration Assay

Substrate competition and bistability. (A) Model extended by addition of substrate X, which binds reversibly to PLS (arrows 4 and 5). After forming a complex of PLS and substrate X (X.PLS), PLS can cleave X and return to the system unbound (arrow 6), whereas the cleaved substrate is degraded/consumed. Catalytic reactions are indicated with dashed lines. (B) The effect of substrate competition on the area of PLS steady-state bistability. The shaded gray area of bistability on the right side of the plot pertains to the original model with ci = 2 and no substrate competition. The broader (unshaded) area of bistability on the left pertains to the extended model with one competing substrate and no explicit cooperativity (ci = 1). Red indicates “going–up” and blue indicates “coming–down”, with changing values of parameter keffPLS. (C) The dependence of bistability on k1, the affinity of the competing substrate toward PLS steady state. Dark lines are stable steady states, and dashed lines are unstable steady states. Black dots indicate SN bifurcations.

Journal: Biophysical Journal

Article Title: Steady States and Dynamics of Urokinase-Mediated Plasmin Activation In Silico and In Vitro

doi: 10.1016/j.bpj.2011.08.054

Figure Lengend Snippet: Substrate competition and bistability. (A) Model extended by addition of substrate X, which binds reversibly to PLS (arrows 4 and 5). After forming a complex of PLS and substrate X (X.PLS), PLS can cleave X and return to the system unbound (arrow 6), whereas the cleaved substrate is degraded/consumed. Catalytic reactions are indicated with dashed lines. (B) The effect of substrate competition on the area of PLS steady-state bistability. The shaded gray area of bistability on the right side of the plot pertains to the original model with ci = 2 and no substrate competition. The broader (unshaded) area of bistability on the left pertains to the extended model with one competing substrate and no explicit cooperativity (ci = 1). Red indicates “going–up” and blue indicates “coming–down”, with changing values of parameter keffPLS. (C) The dependence of bistability on k1, the affinity of the competing substrate toward PLS steady state. Dark lines are stable steady states, and dashed lines are unstable steady states. Black dots indicate SN bifurcations.

Article Snippet: The chromogenic substrate of PLS, S2251 (0.4 mM), with chemical formula H-D-Val-Leu-Lys-pNA.2HCl, was purchased from Chromogenix (Milano, Italy).

Techniques:

Experimental tests of ultrasensitivity and bistability. (A) PLS activity measured experimentally after different doses of recombinant scUPA in the presence of substrate competition (chromogenic substrate) and weak external production of precursor proteins. (B) PLS steady states for different initial levels of PLS/PLG activation and different doses of scUPA.

Journal: Biophysical Journal

Article Title: Steady States and Dynamics of Urokinase-Mediated Plasmin Activation In Silico and In Vitro

doi: 10.1016/j.bpj.2011.08.054

Figure Lengend Snippet: Experimental tests of ultrasensitivity and bistability. (A) PLS activity measured experimentally after different doses of recombinant scUPA in the presence of substrate competition (chromogenic substrate) and weak external production of precursor proteins. (B) PLS steady states for different initial levels of PLS/PLG activation and different doses of scUPA.

Article Snippet: The chromogenic substrate of PLS, S2251 (0.4 mM), with chemical formula H-D-Val-Leu-Lys-pNA.2HCl, was purchased from Chromogenix (Milano, Italy).

Techniques: Activity Assay, Recombinant, Activation Assay

Multivariate pairwise-analysis of patient groups. (a) PLS-DA comparison between the HCM and control groups using blood samples from all three sampling sites (CS, AR, FV) (R 2 X=36%, R 2 Y=41%, Q 2 =18%). (b) PLS-DA comparison between the AS and control groups using blood samples from all three sampling sites (CS, AR, FV) (R 2 X=38%, R 2 Y=64%, Q 2 =54%). (c) PLS-DA comparison between the HCM and AS groups using blood samples from all three sampling sites (CS, AR, FV) (R 2 X=44%, R 2 Y=70%, Q 2 =53%) (d) Random permutation test of the model validity for the model in b. (e) PLS-DA comparison between the control and AS groups using blood samples from the CS (R 2 X=30%, R 2 Y=59%, Q 2 =37%). (f) Box-whisker plots of key metabolites that are discriminatory between the AS and control groups for the model in e. (g) PLS-DA comparison between the HCM and AS groups using blood samples from the CS (R 2 X=29%, R 2 Y=47%; Q 2 =18%). (h) ROC analysis of the predictive capability of the model in e discriminating between AS and control groups.

Journal: bioRxiv

Article Title: Metabolic Profiling of Aortic Stenosis and Hypertrophic Cardiomyopathy Identifies Mechanistic Contrasts in Substrate Utilisation

doi: 10.1101/715680

Figure Lengend Snippet: Multivariate pairwise-analysis of patient groups. (a) PLS-DA comparison between the HCM and control groups using blood samples from all three sampling sites (CS, AR, FV) (R 2 X=36%, R 2 Y=41%, Q 2 =18%). (b) PLS-DA comparison between the AS and control groups using blood samples from all three sampling sites (CS, AR, FV) (R 2 X=38%, R 2 Y=64%, Q 2 =54%). (c) PLS-DA comparison between the HCM and AS groups using blood samples from all three sampling sites (CS, AR, FV) (R 2 X=44%, R 2 Y=70%, Q 2 =53%) (d) Random permutation test of the model validity for the model in b. (e) PLS-DA comparison between the control and AS groups using blood samples from the CS (R 2 X=30%, R 2 Y=59%, Q 2 =37%). (f) Box-whisker plots of key metabolites that are discriminatory between the AS and control groups for the model in e. (g) PLS-DA comparison between the HCM and AS groups using blood samples from the CS (R 2 X=29%, R 2 Y=47%; Q 2 =18%). (h) ROC analysis of the predictive capability of the model in e discriminating between AS and control groups.

Article Snippet: Multivariate data analysis using PCA and PLS was performed in Simca 14.0 (Umetrics, Umeå, Sweden).

Techniques: Comparison, Control, Sampling, Whisker Assay

Predictor variables selected for multivariate orthogonal  partial least square   (O-PLS)  regression model for cervical kinematics

Journal: BMC Musculoskeletal Disorders

Article Title: Kinematics of fast cervical rotations in persons with chronic neck pain: a cross-sectional and reliability study

doi: 10.1186/1471-2474-11-222

Figure Lengend Snippet: Predictor variables selected for multivariate orthogonal partial least square (O-PLS) regression model for cervical kinematics

Article Snippet: SPSS for Windows 15.0 (SPSS Inc., Chicago, Illinois, USA) or SIMCA-P 11.0 (Umetrics AB, Umeå, Sweden) (for PLS-analyses only, see below) was used for statistic calculations and P -values below 0.05 were considered to be significant.

Techniques: Concentration Assay, Activity Assay