codelink human whole genome Search Results


90
Bioarray Inc human codelink whole genome
Human Codelink Whole Genome, supplied by Bioarray 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/result/human codelink whole genome/product/Bioarray Inc
Average 90 stars, based on 1 article reviews
human codelink whole genome - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier

90
Illumina Inc codelink whole human genome arrays
( a ) Members of the network as a classifier of neonatal infection using leave-one-out cross-validation analysis using four independent machine-learning algorithms (red circle, random forest; green triangle, support vector machines; blue+, K nearest neighbour and black x, receiver operator characteristics). ( b ) Flow chart of biomarker classifier validation. Flow chart showing the samples used for classifier generation and the validation results. ( c ) Heat map showing hierarchical clustering of 18 infant samples (9 bacterially infected, 6 control, 3 virally infected) based on the 50 probes that were in common between the classifier gene set and the Affymetrix U219 platform. Hierarchical clustering was based on Euclidean distance. Control, blue; bacterial infected, red; viral infected, black. Classification of bacterial infection is indicated (0=non-infected, 1=infected). ( d ) Comparison of microarray-based classifier and expert assessment for classification of samples from patients with suspected infection. (Top) Comparison of expert assessment, CD69/FCGR1A and the 52-gene classifier on samples scored ‘high’ and ‘low’ likelihood of infection by expert assessment. (Middle) 52-gene classifier prediction and expert assessment of suspected sepsis cases (red=concordance of ‘infection’, blue=concordance of ‘control’, dark grey=discordance of microarray classifier and expert assessment). (Bottom left) Comparison of CD69/FCGR1A and 52-gene classifier of samples scored ‘medium’ likelihood of infection by expert assessment. Classification of bacterial infection is indicated (0=non-infected (pale blue), 1=infected (pink)). (Bottom right) Sensitivity, specificity and accuracy of CD69/FCGR1A and the 52-gene classifier against expert classification for suspected samples from d top. A heat map showing the 30 infant samples of suspected infection based on the 46 probes that were in common between the classifier gene set and the <t>CodeLink</t> platform is shown in . ( e ) Bar plots showing clinical criteria in suspected infection cases as judged by the 52-gene classifier and expert assessment. Days on antibiotics and neutrophil counts are shown for samples based on classification of control (pale blue) and bacterial infection (pink) showing median and standard error of the median. Days on antibiotics, classifier prediction: infected: n =15 (excluding 2 missing values); control: n =12 (excluding 1 missing value). Days on antibiotics, expert assessment: infected: n =5 (excluding 1 missing value); control: n =14 (excluding 1 missing value). Neutrophil count, classifier prediction: infected, n =17; control, n =13. Neutrophil count, expert assessment: infected: n =6; control: n =15.
Codelink Whole Human Genome Arrays, supplied by Illumina 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/result/codelink whole human genome arrays/product/Illumina Inc
Average 90 stars, based on 1 article reviews
codelink whole human genome arrays - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier

90
Inserm Transfert codelink uniset human whole genome bioarrays
( a ) Members of the network as a classifier of neonatal infection using leave-one-out cross-validation analysis using four independent machine-learning algorithms (red circle, random forest; green triangle, support vector machines; blue+, K nearest neighbour and black x, receiver operator characteristics). ( b ) Flow chart of biomarker classifier validation. Flow chart showing the samples used for classifier generation and the validation results. ( c ) Heat map showing hierarchical clustering of 18 infant samples (9 bacterially infected, 6 control, 3 virally infected) based on the 50 probes that were in common between the classifier gene set and the Affymetrix U219 platform. Hierarchical clustering was based on Euclidean distance. Control, blue; bacterial infected, red; viral infected, black. Classification of bacterial infection is indicated (0=non-infected, 1=infected). ( d ) Comparison of microarray-based classifier and expert assessment for classification of samples from patients with suspected infection. (Top) Comparison of expert assessment, CD69/FCGR1A and the 52-gene classifier on samples scored ‘high’ and ‘low’ likelihood of infection by expert assessment. (Middle) 52-gene classifier prediction and expert assessment of suspected sepsis cases (red=concordance of ‘infection’, blue=concordance of ‘control’, dark grey=discordance of microarray classifier and expert assessment). (Bottom left) Comparison of CD69/FCGR1A and 52-gene classifier of samples scored ‘medium’ likelihood of infection by expert assessment. Classification of bacterial infection is indicated (0=non-infected (pale blue), 1=infected (pink)). (Bottom right) Sensitivity, specificity and accuracy of CD69/FCGR1A and the 52-gene classifier against expert classification for suspected samples from d top. A heat map showing the 30 infant samples of suspected infection based on the 46 probes that were in common between the classifier gene set and the <t>CodeLink</t> platform is shown in . ( e ) Bar plots showing clinical criteria in suspected infection cases as judged by the 52-gene classifier and expert assessment. Days on antibiotics and neutrophil counts are shown for samples based on classification of control (pale blue) and bacterial infection (pink) showing median and standard error of the median. Days on antibiotics, classifier prediction: infected: n =15 (excluding 2 missing values); control: n =12 (excluding 1 missing value). Days on antibiotics, expert assessment: infected: n =5 (excluding 1 missing value); control: n =14 (excluding 1 missing value). Neutrophil count, classifier prediction: infected, n =17; control, n =13. Neutrophil count, expert assessment: infected: n =6; control: n =15.
Codelink Uniset Human Whole Genome Bioarrays, supplied by Inserm Transfert, 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/result/codelink uniset human whole genome bioarrays/product/Inserm Transfert
Average 90 stars, based on 1 article reviews
codelink uniset human whole genome bioarrays - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier

90
Amersham Life Sciences Inc human whole-genome microarray amersham codelink
( a ) Members of the network as a classifier of neonatal infection using leave-one-out cross-validation analysis using four independent machine-learning algorithms (red circle, random forest; green triangle, support vector machines; blue+, K nearest neighbour and black x, receiver operator characteristics). ( b ) Flow chart of biomarker classifier validation. Flow chart showing the samples used for classifier generation and the validation results. ( c ) Heat map showing hierarchical clustering of 18 infant samples (9 bacterially infected, 6 control, 3 virally infected) based on the 50 probes that were in common between the classifier gene set and the Affymetrix U219 platform. Hierarchical clustering was based on Euclidean distance. Control, blue; bacterial infected, red; viral infected, black. Classification of bacterial infection is indicated (0=non-infected, 1=infected). ( d ) Comparison of microarray-based classifier and expert assessment for classification of samples from patients with suspected infection. (Top) Comparison of expert assessment, CD69/FCGR1A and the 52-gene classifier on samples scored ‘high’ and ‘low’ likelihood of infection by expert assessment. (Middle) 52-gene classifier prediction and expert assessment of suspected sepsis cases (red=concordance of ‘infection’, blue=concordance of ‘control’, dark grey=discordance of microarray classifier and expert assessment). (Bottom left) Comparison of CD69/FCGR1A and 52-gene classifier of samples scored ‘medium’ likelihood of infection by expert assessment. Classification of bacterial infection is indicated (0=non-infected (pale blue), 1=infected (pink)). (Bottom right) Sensitivity, specificity and accuracy of CD69/FCGR1A and the 52-gene classifier against expert classification for suspected samples from d top. A heat map showing the 30 infant samples of suspected infection based on the 46 probes that were in common between the classifier gene set and the <t>CodeLink</t> platform is shown in . ( e ) Bar plots showing clinical criteria in suspected infection cases as judged by the 52-gene classifier and expert assessment. Days on antibiotics and neutrophil counts are shown for samples based on classification of control (pale blue) and bacterial infection (pink) showing median and standard error of the median. Days on antibiotics, classifier prediction: infected: n =15 (excluding 2 missing values); control: n =12 (excluding 1 missing value). Days on antibiotics, expert assessment: infected: n =5 (excluding 1 missing value); control: n =14 (excluding 1 missing value). Neutrophil count, classifier prediction: infected, n =17; control, n =13. Neutrophil count, expert assessment: infected: n =6; control: n =15.
Human Whole Genome Microarray Amersham Codelink, supplied by Amersham Life Sciences 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/result/human whole-genome microarray amersham codelink/product/Amersham Life Sciences Inc
Average 90 stars, based on 1 article reviews
human whole-genome microarray amersham codelink - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier

90
Bioarray Inc gpl11329 applied codelink human whole genome
( a ) Members of the network as a classifier of neonatal infection using leave-one-out cross-validation analysis using four independent machine-learning algorithms (red circle, random forest; green triangle, support vector machines; blue+, K nearest neighbour and black x, receiver operator characteristics). ( b ) Flow chart of biomarker classifier validation. Flow chart showing the samples used for classifier generation and the validation results. ( c ) Heat map showing hierarchical clustering of 18 infant samples (9 bacterially infected, 6 control, 3 virally infected) based on the 50 probes that were in common between the classifier gene set and the Affymetrix U219 platform. Hierarchical clustering was based on Euclidean distance. Control, blue; bacterial infected, red; viral infected, black. Classification of bacterial infection is indicated (0=non-infected, 1=infected). ( d ) Comparison of microarray-based classifier and expert assessment for classification of samples from patients with suspected infection. (Top) Comparison of expert assessment, CD69/FCGR1A and the 52-gene classifier on samples scored ‘high’ and ‘low’ likelihood of infection by expert assessment. (Middle) 52-gene classifier prediction and expert assessment of suspected sepsis cases (red=concordance of ‘infection’, blue=concordance of ‘control’, dark grey=discordance of microarray classifier and expert assessment). (Bottom left) Comparison of CD69/FCGR1A and 52-gene classifier of samples scored ‘medium’ likelihood of infection by expert assessment. Classification of bacterial infection is indicated (0=non-infected (pale blue), 1=infected (pink)). (Bottom right) Sensitivity, specificity and accuracy of CD69/FCGR1A and the 52-gene classifier against expert classification for suspected samples from d top. A heat map showing the 30 infant samples of suspected infection based on the 46 probes that were in common between the classifier gene set and the <t>CodeLink</t> platform is shown in . ( e ) Bar plots showing clinical criteria in suspected infection cases as judged by the 52-gene classifier and expert assessment. Days on antibiotics and neutrophil counts are shown for samples based on classification of control (pale blue) and bacterial infection (pink) showing median and standard error of the median. Days on antibiotics, classifier prediction: infected: n =15 (excluding 2 missing values); control: n =12 (excluding 1 missing value). Days on antibiotics, expert assessment: infected: n =5 (excluding 1 missing value); control: n =14 (excluding 1 missing value). Neutrophil count, classifier prediction: infected, n =17; control, n =13. Neutrophil count, expert assessment: infected: n =6; control: n =15.
Gpl11329 Applied Codelink Human Whole Genome, supplied by Bioarray 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/result/gpl11329 applied codelink human whole genome/product/Bioarray Inc
Average 90 stars, based on 1 article reviews
gpl11329 applied codelink human whole genome - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier

90
Amersham Life Sciences Inc codelink human whole genome
( a ) Members of the network as a classifier of neonatal infection using leave-one-out cross-validation analysis using four independent machine-learning algorithms (red circle, random forest; green triangle, support vector machines; blue+, K nearest neighbour and black x, receiver operator characteristics). ( b ) Flow chart of biomarker classifier validation. Flow chart showing the samples used for classifier generation and the validation results. ( c ) Heat map showing hierarchical clustering of 18 infant samples (9 bacterially infected, 6 control, 3 virally infected) based on the 50 probes that were in common between the classifier gene set and the Affymetrix U219 platform. Hierarchical clustering was based on Euclidean distance. Control, blue; bacterial infected, red; viral infected, black. Classification of bacterial infection is indicated (0=non-infected, 1=infected). ( d ) Comparison of microarray-based classifier and expert assessment for classification of samples from patients with suspected infection. (Top) Comparison of expert assessment, CD69/FCGR1A and the 52-gene classifier on samples scored ‘high’ and ‘low’ likelihood of infection by expert assessment. (Middle) 52-gene classifier prediction and expert assessment of suspected sepsis cases (red=concordance of ‘infection’, blue=concordance of ‘control’, dark grey=discordance of microarray classifier and expert assessment). (Bottom left) Comparison of CD69/FCGR1A and 52-gene classifier of samples scored ‘medium’ likelihood of infection by expert assessment. Classification of bacterial infection is indicated (0=non-infected (pale blue), 1=infected (pink)). (Bottom right) Sensitivity, specificity and accuracy of CD69/FCGR1A and the 52-gene classifier against expert classification for suspected samples from d top. A heat map showing the 30 infant samples of suspected infection based on the 46 probes that were in common between the classifier gene set and the <t>CodeLink</t> platform is shown in . ( e ) Bar plots showing clinical criteria in suspected infection cases as judged by the 52-gene classifier and expert assessment. Days on antibiotics and neutrophil counts are shown for samples based on classification of control (pale blue) and bacterial infection (pink) showing median and standard error of the median. Days on antibiotics, classifier prediction: infected: n =15 (excluding 2 missing values); control: n =12 (excluding 1 missing value). Days on antibiotics, expert assessment: infected: n =5 (excluding 1 missing value); control: n =14 (excluding 1 missing value). Neutrophil count, classifier prediction: infected, n =17; control, n =13. Neutrophil count, expert assessment: infected: n =6; control: n =15.
Codelink Human Whole Genome, supplied by Amersham Life Sciences 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/result/codelink human whole genome/product/Amersham Life Sciences Inc
Average 90 stars, based on 1 article reviews
codelink human whole genome - by Bioz Stars, 2026-03
90/100 stars
  Buy from Supplier

Image Search Results


( a ) Members of the network as a classifier of neonatal infection using leave-one-out cross-validation analysis using four independent machine-learning algorithms (red circle, random forest; green triangle, support vector machines; blue+, K nearest neighbour and black x, receiver operator characteristics). ( b ) Flow chart of biomarker classifier validation. Flow chart showing the samples used for classifier generation and the validation results. ( c ) Heat map showing hierarchical clustering of 18 infant samples (9 bacterially infected, 6 control, 3 virally infected) based on the 50 probes that were in common between the classifier gene set and the Affymetrix U219 platform. Hierarchical clustering was based on Euclidean distance. Control, blue; bacterial infected, red; viral infected, black. Classification of bacterial infection is indicated (0=non-infected, 1=infected). ( d ) Comparison of microarray-based classifier and expert assessment for classification of samples from patients with suspected infection. (Top) Comparison of expert assessment, CD69/FCGR1A and the 52-gene classifier on samples scored ‘high’ and ‘low’ likelihood of infection by expert assessment. (Middle) 52-gene classifier prediction and expert assessment of suspected sepsis cases (red=concordance of ‘infection’, blue=concordance of ‘control’, dark grey=discordance of microarray classifier and expert assessment). (Bottom left) Comparison of CD69/FCGR1A and 52-gene classifier of samples scored ‘medium’ likelihood of infection by expert assessment. Classification of bacterial infection is indicated (0=non-infected (pale blue), 1=infected (pink)). (Bottom right) Sensitivity, specificity and accuracy of CD69/FCGR1A and the 52-gene classifier against expert classification for suspected samples from d top. A heat map showing the 30 infant samples of suspected infection based on the 46 probes that were in common between the classifier gene set and the CodeLink platform is shown in . ( e ) Bar plots showing clinical criteria in suspected infection cases as judged by the 52-gene classifier and expert assessment. Days on antibiotics and neutrophil counts are shown for samples based on classification of control (pale blue) and bacterial infection (pink) showing median and standard error of the median. Days on antibiotics, classifier prediction: infected: n =15 (excluding 2 missing values); control: n =12 (excluding 1 missing value). Days on antibiotics, expert assessment: infected: n =5 (excluding 1 missing value); control: n =14 (excluding 1 missing value). Neutrophil count, classifier prediction: infected, n =17; control, n =13. Neutrophil count, expert assessment: infected: n =6; control: n =15.

Journal: Nature Communications

Article Title: Identification of a human neonatal immune-metabolic network associated with bacterial infection

doi: 10.1038/ncomms5649

Figure Lengend Snippet: ( a ) Members of the network as a classifier of neonatal infection using leave-one-out cross-validation analysis using four independent machine-learning algorithms (red circle, random forest; green triangle, support vector machines; blue+, K nearest neighbour and black x, receiver operator characteristics). ( b ) Flow chart of biomarker classifier validation. Flow chart showing the samples used for classifier generation and the validation results. ( c ) Heat map showing hierarchical clustering of 18 infant samples (9 bacterially infected, 6 control, 3 virally infected) based on the 50 probes that were in common between the classifier gene set and the Affymetrix U219 platform. Hierarchical clustering was based on Euclidean distance. Control, blue; bacterial infected, red; viral infected, black. Classification of bacterial infection is indicated (0=non-infected, 1=infected). ( d ) Comparison of microarray-based classifier and expert assessment for classification of samples from patients with suspected infection. (Top) Comparison of expert assessment, CD69/FCGR1A and the 52-gene classifier on samples scored ‘high’ and ‘low’ likelihood of infection by expert assessment. (Middle) 52-gene classifier prediction and expert assessment of suspected sepsis cases (red=concordance of ‘infection’, blue=concordance of ‘control’, dark grey=discordance of microarray classifier and expert assessment). (Bottom left) Comparison of CD69/FCGR1A and 52-gene classifier of samples scored ‘medium’ likelihood of infection by expert assessment. Classification of bacterial infection is indicated (0=non-infected (pale blue), 1=infected (pink)). (Bottom right) Sensitivity, specificity and accuracy of CD69/FCGR1A and the 52-gene classifier against expert classification for suspected samples from d top. A heat map showing the 30 infant samples of suspected infection based on the 46 probes that were in common between the classifier gene set and the CodeLink platform is shown in . ( e ) Bar plots showing clinical criteria in suspected infection cases as judged by the 52-gene classifier and expert assessment. Days on antibiotics and neutrophil counts are shown for samples based on classification of control (pale blue) and bacterial infection (pink) showing median and standard error of the median. Days on antibiotics, classifier prediction: infected: n =15 (excluding 2 missing values); control: n =12 (excluding 1 missing value). Days on antibiotics, expert assessment: infected: n =5 (excluding 1 missing value); control: n =14 (excluding 1 missing value). Neutrophil count, classifier prediction: infected, n =17; control, n =13. Neutrophil count, expert assessment: infected: n =6; control: n =15.

Article Snippet: In addition to the Illumina microarray analysis, we examined a subset of 42 of these samples (18 infected, 24 controls) using CodeLink Whole Human Genome arrays, referred to as ‘platform test set’.

Techniques: Infection, Plasmid Preparation, Biomarker Assay, Microarray