Principal component analysis (PCA) is applied on extracted data of digital holograms of growing cell clusters. We show that PCA can be used to discriminate control and tumorigenic samples
A method for quantification of images of immunohistochemically stained cell nuclei by computing area...
PCA of the quantile normalized dataset consisting of 32 mouse uterine RNA samples. The colours repre...
In early drug discovery and the study of the effects of new chemical compounds on cancer cells, the ...
Principal component analysis (PCA) is applied on extracted data of digital holograms of growing cell...
<p><i>A</i>, The PCA results are provided as two-dimensional representations based on contribution s...
(A) A total of 128 variables (listed in Methods and S2 Table) related to morphology, location, proli...
<p>a. In the discovery dataset, the 5 tumor and 1 control methylation classes were represented by th...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
Cell registration by artificial neural networks (ANNs) in combination with principal component analy...
<p>(A) Texture measurements from microcarrier seeded with 10 cells per bead and incubated for 2.5 ho...
AbstractBy using principal components analysis (PCA) we demonstrate here that the information releva...
The calcium-imaging technique allows us to record movies of brain activity in the antennal lobe of t...
<p>The color codes for each time point are shown on the top right corner. The three axes PC1, PC2, a...
Background. The calcium-imaging technique allows us to record movies of brain activity in the antenn...
Duplicate biological samples of matched normal and cancerous colon tissue from five anonymized patie...
A method for quantification of images of immunohistochemically stained cell nuclei by computing area...
PCA of the quantile normalized dataset consisting of 32 mouse uterine RNA samples. The colours repre...
In early drug discovery and the study of the effects of new chemical compounds on cancer cells, the ...
Principal component analysis (PCA) is applied on extracted data of digital holograms of growing cell...
<p><i>A</i>, The PCA results are provided as two-dimensional representations based on contribution s...
(A) A total of 128 variables (listed in Methods and S2 Table) related to morphology, location, proli...
<p>a. In the discovery dataset, the 5 tumor and 1 control methylation classes were represented by th...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
Cell registration by artificial neural networks (ANNs) in combination with principal component analy...
<p>(A) Texture measurements from microcarrier seeded with 10 cells per bead and incubated for 2.5 ho...
AbstractBy using principal components analysis (PCA) we demonstrate here that the information releva...
The calcium-imaging technique allows us to record movies of brain activity in the antennal lobe of t...
<p>The color codes for each time point are shown on the top right corner. The three axes PC1, PC2, a...
Background. The calcium-imaging technique allows us to record movies of brain activity in the antenn...
Duplicate biological samples of matched normal and cancerous colon tissue from five anonymized patie...
A method for quantification of images of immunohistochemically stained cell nuclei by computing area...
PCA of the quantile normalized dataset consisting of 32 mouse uterine RNA samples. The colours repre...
In early drug discovery and the study of the effects of new chemical compounds on cancer cells, the ...
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