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nls function  (RStudio)

 
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    RStudio nls function
    Nls Function, supplied by RStudio, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/routine+for+impulsed+fitting/nls+function/pmc09897472-236-1-10
    Average 90 stars, based on 1 article reviews
    nls function - by Bioz Stars, 2026-11
    90/100 stars

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    Related Articles

    Software:

    Article Title: Deciphering Seasonal Patterns in Animal Feeding: A Mechanistic Approach to Analyzing the Restricted Growth of Iberian Pigs.
    Article Snippet: .. The lm and nls functions in RStudio (R software environment, version R.4.4.1) were used for model fitting, and persp3d and trans3d were employed to create surface plots (Table S1)) and Excel (Microsoft Office, version 2013) was used for the statistical analysis. ..

    other:

    Article Title: Analyzing the Life History of Caimans: The Growth Dynamics of Caiman latirostris From an Osteohistological Approach.
    Article Snippet: To generate the growth curves based on SVL and body mass versus the maximum estimated age per individual, we use the “nlsr” package (Nash and Murdoch 2017) in Rstudio (R Core Team 2018) taken from Viotto, Navarro, and Piña (2020).

    Article Title: Applicability of MDR1 Overexpressing Abcb1KO-MDCKII Cell Lines for Investigating In Vitro Species Differences and Brain Penetration Prediction
    Article Snippet: The regression was performed in RStudio (version 2023.12.0) using the nls_multstart() function from the nls.multstart package [ ], and the best fit was determined based on the best Akaike information criterion (AIC).

    Article Title: Impact of pre-growth and storage conditions on the survival of Listeria monocytogenes in acidic baby fruit purees: Implications for food safety and consumer practices.
    Article Snippet: Fitting growth and inactivation parameters Inactivation and growth curves were fitted by using the ‘nls’ function in R Studio (version 2024.09.1).

    Article Title: Zebrafish as a model organism to study sporadic Alzheimer's disease: Behavioural, biochemical and histological validation.
    Article Snippet: Alzheimer’s disease (AD) is a global burden to the healthcare system with no viable treatment options till date.. Rodents and primates have been extensively used as models for understanding AD pathogenesis and identifying therapeutic targets.. However, the focus is now shifting towards developing alternate models.

    Article Title: Effect of vaccination against foot-and-mouth disease during mid-pregnancy on the neutralizing antibody response in the cow.
    Article Snippet: As pregnancy can adversely affect the immune response of vaccination against foot and mouth disease virus (FMDV) due to physiological immunosuppressive milieu, we tested the effect of FMDV vaccination during midgestation on the antibody response.. Pregnant and non-pregnant cows of crossbred and indigenous breed (n = 28/ group) were vaccinated with inactivated FMD vaccine covering O, A, and Asia1 serotypes and the sera were harvested at weekly interval till day 42 post-vaccination.. Virus neutralization test (VNT) was done and the analysis of log10 VN50 antibody titer by mixed model ANOVA indicated that pregnancy did not significantly affect the log10 VN50 titer for FMDV serotype O and Asia1.

    Article Title: Analyzing the Life History of Caimans: The Growth Dynamics of Caiman latirostris From an Osteohistological Approach
    Article Snippet: To generate the growth curves based on SVL and body mass versus the maximum estimated age per individual, we use the “nlsr” package (Nash and Murdoch ) in Rstudio (R Core Team ) taken from Viotto, Navarro, and Piña ( ).



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    routine for impulsed fitting  (MathWorks Inc)
    90
    MathWorks Inc routine for impulsed fitting
    Representative images of microstructural mapping and correlation between the microstructural mapping results and histopathologic findings. (a) Representative images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case, including diameter, V in , D ex , cellularity fitted from <t>IMPULSED</t> and the ADC maps. Red arrows and white dashed lines indicate tumor ROI. Corresponding diffusion‐weighted images ( b = 1000 s/mm 2 ) at the similar axial locations are shown in the first column. (b) Correlation between t d ‐dMRI‐based cellularity and nuclei counting. Nuclei counting images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case quantified with QuPath in H&E‐stained slices (original magnification: ×400, scale bar: 50 μm). Graph demonstrating satisfactory positive correlation between cellularity and histopathology‐based nuclei counting in representative participants ( n = 13). ADC, Apparent diffusion coefficient; ΔADC1 and ΔADC2, ratios of change in ADC values between OGSE and PGSE sequences; ADC N1 , ADC N2 , ADC PGSE , ADC from OGSE N1 , OGSE N2 and PGSE, respectively; ROI, regions of interest; H&E, hematoxylin and eosin.
    Routine For Impulsed Fitting, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/routine+for+impulsed+fitting/pmc12127095-93-4-1
    Average 90 stars, based on 1 article reviews
    routine for impulsed fitting - by Bioz Stars, 2026-11
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Representative images of microstructural mapping and correlation between the microstructural mapping results and histopathologic findings. (a) Representative images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case, including diameter, V in , D ex , cellularity fitted from IMPULSED and the ADC maps. Red arrows and white dashed lines indicate tumor ROI. Corresponding diffusion‐weighted images ( b = 1000 s/mm 2 ) at the similar axial locations are shown in the first column. (b) Correlation between t d ‐dMRI‐based cellularity and nuclei counting. Nuclei counting images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case quantified with QuPath in H&E‐stained slices (original magnification: ×400, scale bar: 50 μm). Graph demonstrating satisfactory positive correlation between cellularity and histopathology‐based nuclei counting in representative participants ( n = 13). ADC, Apparent diffusion coefficient; ΔADC1 and ΔADC2, ratios of change in ADC values between OGSE and PGSE sequences; ADC N1 , ADC N2 , ADC PGSE , ADC from OGSE N1 , OGSE N2 and PGSE, respectively; ROI, regions of interest; H&E, hematoxylin and eosin.

    Journal: Cancer Science

    Article Title: Risk Stratification Prediction of Endometrial Cancer Using Microstructural Mapping Based on Time‐Dependent Diffusion MRI

    doi: 10.1111/cas.70036

    Figure Lengend Snippet: Representative images of microstructural mapping and correlation between the microstructural mapping results and histopathologic findings. (a) Representative images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case, including diameter, V in , D ex , cellularity fitted from IMPULSED and the ADC maps. Red arrows and white dashed lines indicate tumor ROI. Corresponding diffusion‐weighted images ( b = 1000 s/mm 2 ) at the similar axial locations are shown in the first column. (b) Correlation between t d ‐dMRI‐based cellularity and nuclei counting. Nuclei counting images of a low‐risk and low‐proliferation case and a high‐risk and high‐proliferation case quantified with QuPath in H&E‐stained slices (original magnification: ×400, scale bar: 50 μm). Graph demonstrating satisfactory positive correlation between cellularity and histopathology‐based nuclei counting in representative participants ( n = 13). ADC, Apparent diffusion coefficient; ΔADC1 and ΔADC2, ratios of change in ADC values between OGSE and PGSE sequences; ADC N1 , ADC N2 , ADC PGSE , ADC from OGSE N1 , OGSE N2 and PGSE, respectively; ROI, regions of interest; H&E, hematoxylin and eosin.

    Article Snippet: The MATLAB routine for IMPULSED fitting is provided at https://github.com/wjgxw/ogse .

    Techniques: Diffusion-based Assay, Staining, Histopathology