<p>The figure shows paired microdialysate and plasma derived cytokine data from 12 patients. Principal component analysis has been used to identify the first 2 principal components which explain 33.4% of the variation within the dataset. Part A is a scores plot which shows the scores for each observation on each of the principal components and even in this unsupervised model a clear separation between microdialysis and plasma derived cytokines is apparent. Part B is a loading plot which shows the cytokines responsible for the differences between the two biological compartments.</p
<p>(A) Two-dimensional PCA of miRs, derived from 20 patients with NSCLC and 10 tissue samples from n...
<p>PC1 and PC2 explain 27.7% and 15.7% of the variability in data, respectively (total 43.4%). The p...
<p>(A) PCA score plot showing a three dimensional visualization of similarities and differences betw...
<p>The figure shows cerebral microdialysis derived cytokine data from 12 patients (A–L) pooled into ...
<p>This figure shows paired microdialysate and plasma derived cytokine data from 12 patients as in <...
In the score plot (left panel) each dot represents one analyzed sample and similar phospholipid prof...
<p>Figure (A) shows the variance of each of the principal component scores amongst the 90 patients s...
<p>Patients with (red dots) and without (blue dots) SIRS are represented according to the first thre...
PCA plot shows the cytokine ELISA data from the combination of two different experimental groups TBL...
<p>Principal component analysis of the micro-array data sets for paired blood (red circles) and pulm...
The x, y, and z axes are the first, second, and third components that together capture most of the v...
There is a growing realisation that neuro-inflammation plays a fundamental role in the pathology of ...
<p>A) Principal component analysis shows a clear distinction between DBA and control cytosols with t...
<p>(a) The mean value of the cumulative percentage of the variance in the data explained is plotted ...
<p>A principal component analysis was performed on the 12 blood transcriptome data sets which remain...
<p>(A) Two-dimensional PCA of miRs, derived from 20 patients with NSCLC and 10 tissue samples from n...
<p>PC1 and PC2 explain 27.7% and 15.7% of the variability in data, respectively (total 43.4%). The p...
<p>(A) PCA score plot showing a three dimensional visualization of similarities and differences betw...
<p>The figure shows cerebral microdialysis derived cytokine data from 12 patients (A–L) pooled into ...
<p>This figure shows paired microdialysate and plasma derived cytokine data from 12 patients as in <...
In the score plot (left panel) each dot represents one analyzed sample and similar phospholipid prof...
<p>Figure (A) shows the variance of each of the principal component scores amongst the 90 patients s...
<p>Patients with (red dots) and without (blue dots) SIRS are represented according to the first thre...
PCA plot shows the cytokine ELISA data from the combination of two different experimental groups TBL...
<p>Principal component analysis of the micro-array data sets for paired blood (red circles) and pulm...
The x, y, and z axes are the first, second, and third components that together capture most of the v...
There is a growing realisation that neuro-inflammation plays a fundamental role in the pathology of ...
<p>A) Principal component analysis shows a clear distinction between DBA and control cytosols with t...
<p>(a) The mean value of the cumulative percentage of the variance in the data explained is plotted ...
<p>A principal component analysis was performed on the 12 blood transcriptome data sets which remain...
<p>(A) Two-dimensional PCA of miRs, derived from 20 patients with NSCLC and 10 tissue samples from n...
<p>PC1 and PC2 explain 27.7% and 15.7% of the variability in data, respectively (total 43.4%). The p...
<p>(A) PCA score plot showing a three dimensional visualization of similarities and differences betw...