matlab version 7.15 Search Results


component runtime mcr 32 bits version 7.15 or later  (MathWorks Inc)
90
MathWorks Inc component runtime mcr 32 bits version 7.15 or later
Component Runtime Mcr 32 Bits Version 7.15 Or Later, 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
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matlab version 7.15  (MathWorks Inc)
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MathWorks Inc matlab version 7.15
Matlab Version 7.15, 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
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gaussian process for machine learning (gpml) toolbox version 3.2  (MathWorks Inc)
90
MathWorks Inc gaussian process for machine learning (gpml) toolbox version 3.2
Analysis of the confidence intervals predicted on (left) the adenosine receptors and (right) aminergic GPCRs external sets. The percentages of annotated values lying within the intervals of confidence of 68%, 80%, 95% and 99% (ordinate axis) are depicted versus the size of the intervals. The blue line defines the theoretical proportionality between the size of confidence intervals and the number of points within the intervals, in the frame of the <t>Gaussian</t> cumulative function. The radial, PUK, and normalized polynomial (NP) kernels are in close conformity with the cumulative Gaussian distribution in both datasets, while the Laplacian and Bessel exhibit a diverse behavior depending on the dataset. Therefore, GP provide prediction errors in agreement with the Cumulative Gaussian distribution which can be reliably used to define intervals of confidence for the predictions.
Gaussian Process For Machine Learning (Gpml) Toolbox Version 3.2, 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
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stata v15.1  (STATA Corporation)
90
STATA Corporation stata v15.1
Analysis of the confidence intervals predicted on (left) the adenosine receptors and (right) aminergic GPCRs external sets. The percentages of annotated values lying within the intervals of confidence of 68%, 80%, 95% and 99% (ordinate axis) are depicted versus the size of the intervals. The blue line defines the theoretical proportionality between the size of confidence intervals and the number of points within the intervals, in the frame of the <t>Gaussian</t> cumulative function. The radial, PUK, and normalized polynomial (NP) kernels are in close conformity with the cumulative Gaussian distribution in both datasets, while the Laplacian and Bessel exhibit a diverse behavior depending on the dataset. Therefore, GP provide prediction errors in agreement with the Cumulative Gaussian distribution which can be reliably used to define intervals of confidence for the predictions.
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matlab r2014b environment  (MathWorks Inc)
90
MathWorks Inc matlab r2014b environment
Analysis of the confidence intervals predicted on (left) the adenosine receptors and (right) aminergic GPCRs external sets. The percentages of annotated values lying within the intervals of confidence of 68%, 80%, 95% and 99% (ordinate axis) are depicted versus the size of the intervals. The blue line defines the theoretical proportionality between the size of confidence intervals and the number of points within the intervals, in the frame of the <t>Gaussian</t> cumulative function. The radial, PUK, and normalized polynomial (NP) kernels are in close conformity with the cumulative Gaussian distribution in both datasets, while the Laplacian and Bessel exhibit a diverse behavior depending on the dataset. Therefore, GP provide prediction errors in agreement with the Cumulative Gaussian distribution which can be reliably used to define intervals of confidence for the predictions.
Matlab R2014b Environment, 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
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anti mouse cy3 jackson immuno research  (Jackson Immuno)
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Jackson Immuno anti mouse cy3 jackson immuno research
Analysis of the confidence intervals predicted on (left) the adenosine receptors and (right) aminergic GPCRs external sets. The percentages of annotated values lying within the intervals of confidence of 68%, 80%, 95% and 99% (ordinate axis) are depicted versus the size of the intervals. The blue line defines the theoretical proportionality between the size of confidence intervals and the number of points within the intervals, in the frame of the <t>Gaussian</t> cumulative function. The radial, PUK, and normalized polynomial (NP) kernels are in close conformity with the cumulative Gaussian distribution in both datasets, while the Laplacian and Bessel exhibit a diverse behavior depending on the dataset. Therefore, GP provide prediction errors in agreement with the Cumulative Gaussian distribution which can be reliably used to define intervals of confidence for the predictions.
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gfp  (Thermo Fisher)
90
Thermo Fisher gfp
Analysis of the confidence intervals predicted on (left) the adenosine receptors and (right) aminergic GPCRs external sets. The percentages of annotated values lying within the intervals of confidence of 68%, 80%, 95% and 99% (ordinate axis) are depicted versus the size of the intervals. The blue line defines the theoretical proportionality between the size of confidence intervals and the number of points within the intervals, in the frame of the <t>Gaussian</t> cumulative function. The radial, PUK, and normalized polynomial (NP) kernels are in close conformity with the cumulative Gaussian distribution in both datasets, while the Laplacian and Bessel exhibit a diverse behavior depending on the dataset. Therefore, GP provide prediction errors in agreement with the Cumulative Gaussian distribution which can be reliably used to define intervals of confidence for the predictions.
Gfp, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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anti goat cy5 jackson immuno research  (Jackson Immuno)
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Jackson Immuno anti goat cy5 jackson immuno research
Analysis of the confidence intervals predicted on (left) the adenosine receptors and (right) aminergic GPCRs external sets. The percentages of annotated values lying within the intervals of confidence of 68%, 80%, 95% and 99% (ordinate axis) are depicted versus the size of the intervals. The blue line defines the theoretical proportionality between the size of confidence intervals and the number of points within the intervals, in the frame of the <t>Gaussian</t> cumulative function. The radial, PUK, and normalized polynomial (NP) kernels are in close conformity with the cumulative Gaussian distribution in both datasets, while the Laplacian and Bessel exhibit a diverse behavior depending on the dataset. Therefore, GP provide prediction errors in agreement with the Cumulative Gaussian distribution which can be reliably used to define intervals of confidence for the predictions.
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anti goat cy3 jackson immuno research  (Jackson Immuno)
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Jackson Immuno anti goat cy3 jackson immuno research
Analysis of the confidence intervals predicted on (left) the adenosine receptors and (right) aminergic GPCRs external sets. The percentages of annotated values lying within the intervals of confidence of 68%, 80%, 95% and 99% (ordinate axis) are depicted versus the size of the intervals. The blue line defines the theoretical proportionality between the size of confidence intervals and the number of points within the intervals, in the frame of the <t>Gaussian</t> cumulative function. The radial, PUK, and normalized polynomial (NP) kernels are in close conformity with the cumulative Gaussian distribution in both datasets, while the Laplacian and Bessel exhibit a diverse behavior depending on the dataset. Therefore, GP provide prediction errors in agreement with the Cumulative Gaussian distribution which can be reliably used to define intervals of confidence for the predictions.
Anti Goat Cy3 Jackson Immuno Research, supplied by Jackson Immuno, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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aav5 aav1 flex tdtomato addgene  (Addgene inc)
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Addgene inc aav5 aav1 flex tdtomato addgene
Analysis of the confidence intervals predicted on (left) the adenosine receptors and (right) aminergic GPCRs external sets. The percentages of annotated values lying within the intervals of confidence of 68%, 80%, 95% and 99% (ordinate axis) are depicted versus the size of the intervals. The blue line defines the theoretical proportionality between the size of confidence intervals and the number of points within the intervals, in the frame of the <t>Gaussian</t> cumulative function. The radial, PUK, and normalized polynomial (NP) kernels are in close conformity with the cumulative Gaussian distribution in both datasets, while the Laplacian and Bessel exhibit a diverse behavior depending on the dataset. Therefore, GP provide prediction errors in agreement with the Cumulative Gaussian distribution which can be reliably used to define intervals of confidence for the predictions.
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rat anti-somatostatin  (Millipore)
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Millipore rat anti-somatostatin
Analysis of the confidence intervals predicted on (left) the adenosine receptors and (right) aminergic GPCRs external sets. The percentages of annotated values lying within the intervals of confidence of 68%, 80%, 95% and 99% (ordinate axis) are depicted versus the size of the intervals. The blue line defines the theoretical proportionality between the size of confidence intervals and the number of points within the intervals, in the frame of the <t>Gaussian</t> cumulative function. The radial, PUK, and normalized polynomial (NP) kernels are in close conformity with the cumulative Gaussian distribution in both datasets, while the Laplacian and Bessel exhibit a diverse behavior depending on the dataset. Therefore, GP provide prediction errors in agreement with the Cumulative Gaussian distribution which can be reliably used to define intervals of confidence for the predictions.
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v292 1 aav5 hsyn flex chrimsonr tdtomato addgene  (Addgene inc)
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Addgene inc v292 1 aav5 hsyn flex chrimsonr tdtomato addgene
Analysis of the confidence intervals predicted on (left) the adenosine receptors and (right) aminergic GPCRs external sets. The percentages of annotated values lying within the intervals of confidence of 68%, 80%, 95% and 99% (ordinate axis) are depicted versus the size of the intervals. The blue line defines the theoretical proportionality between the size of confidence intervals and the number of points within the intervals, in the frame of the <t>Gaussian</t> cumulative function. The radial, PUK, and normalized polynomial (NP) kernels are in close conformity with the cumulative Gaussian distribution in both datasets, while the Laplacian and Bessel exhibit a diverse behavior depending on the dataset. Therefore, GP provide prediction errors in agreement with the Cumulative Gaussian distribution which can be reliably used to define intervals of confidence for the predictions.
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Image Search Results


Analysis of the confidence intervals predicted on (left) the adenosine receptors and (right) aminergic GPCRs external sets. The percentages of annotated values lying within the intervals of confidence of 68%, 80%, 95% and 99% (ordinate axis) are depicted versus the size of the intervals. The blue line defines the theoretical proportionality between the size of confidence intervals and the number of points within the intervals, in the frame of the Gaussian cumulative function. The radial, PUK, and normalized polynomial (NP) kernels are in close conformity with the cumulative Gaussian distribution in both datasets, while the Laplacian and Bessel exhibit a diverse behavior depending on the dataset. Therefore, GP provide prediction errors in agreement with the Cumulative Gaussian distribution which can be reliably used to define intervals of confidence for the predictions.

Journal: Journal of Cheminformatics

Article Title: Proteochemometric modeling in a Bayesian framework

doi: 10.1186/1758-2946-6-35

Figure Lengend Snippet: Analysis of the confidence intervals predicted on (left) the adenosine receptors and (right) aminergic GPCRs external sets. The percentages of annotated values lying within the intervals of confidence of 68%, 80%, 95% and 99% (ordinate axis) are depicted versus the size of the intervals. The blue line defines the theoretical proportionality between the size of confidence intervals and the number of points within the intervals, in the frame of the Gaussian cumulative function. The radial, PUK, and normalized polynomial (NP) kernels are in close conformity with the cumulative Gaussian distribution in both datasets, while the Laplacian and Bessel exhibit a diverse behavior depending on the dataset. Therefore, GP provide prediction errors in agreement with the Cumulative Gaussian distribution which can be reliably used to define intervals of confidence for the predictions.

Article Snippet: Likewise, The Gaussian Process for Machine Learning (GPML) Toolbox version 3.2 [ ] was used to build GP models in Matlab version 7.15 [ ] to assess the importance of ligand descriptors (Automatic Relevance Determination).

Techniques: