Review



composite z score  (CogState Ltd)

 
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
    • 90
      Buy from Supplier

    Structured Review

    CogState Ltd composite z score
    Composite Z Score, supplied by CogState Ltd, 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/z-score/cogstate+composite+score/nct04939597-26-7-7
    Average 90 stars, based on 1 article reviews
    composite z score - by Bioz Stars, 2026-09
    90/100 stars

    Images

    Related Articles

    other:

    Article Title: Effects of a 6-month dual-task, power-based exercise program on cognitive function, neurological and inflammatory markers in older adults: secondary analysis of a cluster randomised controlled trial
    Article Snippet: Participants with a Z-score ≤ -1.0 SD on at least three of the five individual cognitive tests were classified as having mild cognitive impairment (MCI) (based on communication with CogState Pty Ltd and [ ]).

    Article Title: Effects of a 6-month dual-task, power-based exercise program on cognitive function, neurological and inflammatory markers in older adults: secondary analysis of a cluster randomised controlled trial.
    Article Snippet: Participants with a Z-score ≤ -1.0 SD on at least three of the five individual cognitive tests were classified as having mild cognitive impairment (MCI) (based on communication with CogState Pty Ltd and [29]).

    Article Title: Cognitive Functioning and Psychosocial Outcomes in Adults with Complex Congenital Heart Disease: A Cross-sectional Pilot Study.
    Article Snippet: In other clinical cohorts, a z-score of >1 SD below normative mean on Cogstate demonstrates optimal sensitivity for detecting mild cognitive decline [31].



    Similar Products

    composite z score  (CogState Ltd)
    90
    CogState Ltd composite z score
    Composite Z Score, supplied by CogState Ltd, 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/z-score/cogstate+composite+score/nct04939597-26-7-7
    Average 90 stars, based on 1 article reviews
    composite z score - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier
    z score method  (Stouffer Industries)
    86
    Stouffer Industries z score method
    Z Score Method, supplied by Stouffer Industries, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/z-score/score+z/pm42278322-413-11-10
    Average 86 stars, based on 1 article reviews
    z score method - by Bioz Stars, 2026-09
    86/100 stars
    		  Buy from Supplier
    z score  (Stouffer Industries)
    86
    Stouffer Industries z score
    Z Score, supplied by Stouffer Industries, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/z-score/score+z/10__1113_slash_ep093387-217-13-12
    Average 86 stars, based on 1 article reviews
    z score - by Bioz Stars, 2026-09
    86/100 stars
    		  Buy from Supplier
    stouffer z score  (Stouffer Industries)
    86
    Stouffer Industries stouffer z score
    Study overview: multi-cohort paired transcriptomics of checkpoint dynamics. (a) Study design schematic. Paired tumor biopsies were collected before and after ICB therapy (anti-PD-1 or anti-PD-1/anti-CTLA-4), and transcriptomic profiles were used for checkpoint dynamics analysis and clinical response association. (b) Dataset overview. Bar chart showing the number of paired patients (pre + post biopsies) per cohort and cancer type. n = 42 from GSE91061 (melanoma), n = 11 from Sade-Feldman2018/ GSE120575 (melanoma), n = 11 from Yost2019/ GSE123813 (BCC); total n = 64. (c) Meta-analysis mean fold-change <t>(Z-score)</t> per checkpoint gene across all datasets. Asterisks indicate genes reaching padj < 0.05. Genes are colored by functional category: inhibitory checkpoints (red), co-stimulatory molecules (teal), metabolic checkpoints (salmon), exhaustion markers (blue-grey). (d) Six-step analysis pipeline: data collection (4 cohorts, n = 64 paired) → pseudo-bulk aggregation and Z-score batch correction → paired DE analysis (Stouffer Z meta-analysis) → network rewiring (co-expression, hub shift) → ensemble model (AUC = 0.812, n = 38 genes) → clinical implication (combination therapy).
    Stouffer Z Score, supplied by Stouffer Industries, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/z-score/score+z/pmc13253502-51-6-6
    Average 86 stars, based on 1 article reviews
    stouffer z score - by Bioz Stars, 2026-09
    86/100 stars
    		  Buy from Supplier
    stouffer z score meta analysis  (Stouffer Industries)
    86
    Stouffer Industries stouffer z score meta analysis
    Study overview: multi-cohort paired transcriptomics of checkpoint dynamics. (a) Study design schematic. Paired tumor biopsies were collected before and after ICB therapy (anti-PD-1 or anti-PD-1/anti-CTLA-4), and transcriptomic profiles were used for checkpoint dynamics analysis and clinical response association. (b) Dataset overview. Bar chart showing the number of paired patients (pre + post biopsies) per cohort and cancer type. n = 42 from GSE91061 (melanoma), n = 11 from Sade-Feldman2018/ GSE120575 (melanoma), n = 11 from Yost2019/ GSE123813 (BCC); total n = 64. <t>(c)</t> <t>Meta-analysis</t> mean fold-change <t>(Z-score)</t> per checkpoint gene across all datasets. Asterisks indicate genes reaching padj < 0.05. Genes are colored by functional category: inhibitory checkpoints (red), co-stimulatory molecules (teal), metabolic checkpoints (salmon), exhaustion markers (blue-grey). (d) Six-step analysis pipeline: data collection (4 cohorts, n = 64 paired) → pseudo-bulk aggregation and Z-score batch correction → paired DE analysis (Stouffer Z meta-analysis) → network rewiring (co-expression, hub shift) → ensemble model (AUC = 0.812, n = 38 genes) → clinical implication (combination therapy).
    Stouffer Z Score Meta Analysis, supplied by Stouffer Industries, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/z-score/score+z/pmc13253502-31-14-14
    Average 86 stars, based on 1 article reviews
    stouffer z score meta analysis - by Bioz Stars, 2026-09
    86/100 stars
    		  Buy from Supplier
    stouffer s z score  (Stouffer Industries)
    86
    Stouffer Industries stouffer s z score
    Study overview: multi-cohort paired transcriptomics of checkpoint dynamics. (a) Study design schematic. Paired tumor biopsies were collected before and after ICB therapy (anti-PD-1 or anti-PD-1/anti-CTLA-4), and transcriptomic profiles were used for checkpoint dynamics analysis and clinical response association. (b) Dataset overview. Bar chart showing the number of paired patients (pre + post biopsies) per cohort and cancer type. n = 42 from GSE91061 (melanoma), n = 11 from Sade-Feldman2018/ GSE120575 (melanoma), n = 11 from Yost2019/ GSE123813 (BCC); total n = 64. <t>(c)</t> <t>Meta-analysis</t> mean fold-change <t>(Z-score)</t> per checkpoint gene across all datasets. Asterisks indicate genes reaching padj < 0.05. Genes are colored by functional category: inhibitory checkpoints (red), co-stimulatory molecules (teal), metabolic checkpoints (salmon), exhaustion markers (blue-grey). (d) Six-step analysis pipeline: data collection (4 cohorts, n = 64 paired) → pseudo-bulk aggregation and Z-score batch correction → paired DE analysis (Stouffer Z meta-analysis) → network rewiring (co-expression, hub shift) → ensemble model (AUC = 0.812, n = 38 genes) → clinical implication (combination therapy).
    Stouffer S Z Score, supplied by Stouffer Industries, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/z-score/score+z/pm42167238-406-10-10
    Average 86 stars, based on 1 article reviews
    stouffer s z score - by Bioz Stars, 2026-09
    86/100 stars
    		  Buy from Supplier
    single lscte121 z score  (Stouffer Industries)
    86
    Stouffer Industries single lscte121 z score
    Study overview: multi-cohort paired transcriptomics of checkpoint dynamics. (a) Study design schematic. Paired tumor biopsies were collected before and after ICB therapy (anti-PD-1 or anti-PD-1/anti-CTLA-4), and transcriptomic profiles were used for checkpoint dynamics analysis and clinical response association. (b) Dataset overview. Bar chart showing the number of paired patients (pre + post biopsies) per cohort and cancer type. n = 42 from GSE91061 (melanoma), n = 11 from Sade-Feldman2018/ GSE120575 (melanoma), n = 11 from Yost2019/ GSE123813 (BCC); total n = 64. <t>(c)</t> <t>Meta-analysis</t> mean fold-change <t>(Z-score)</t> per checkpoint gene across all datasets. Asterisks indicate genes reaching padj < 0.05. Genes are colored by functional category: inhibitory checkpoints (red), co-stimulatory molecules (teal), metabolic checkpoints (salmon), exhaustion markers (blue-grey). (d) Six-step analysis pipeline: data collection (4 cohorts, n = 64 paired) → pseudo-bulk aggregation and Z-score batch correction → paired DE analysis (Stouffer Z meta-analysis) → network rewiring (co-expression, hub shift) → ensemble model (AUC = 0.812, n = 38 genes) → clinical implication (combination therapy).
    Single Lscte121 Z Score, supplied by Stouffer Industries, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/z-score/lscte121+score+single+z/pm42082719-116-4-22
    Average 86 stars, based on 1 article reviews
    single lscte121 z score - by Bioz Stars, 2026-09
    86/100 stars
    		  Buy from Supplier

    Image Search Results


    Study overview: multi-cohort paired transcriptomics of checkpoint dynamics. (a) Study design schematic. Paired tumor biopsies were collected before and after ICB therapy (anti-PD-1 or anti-PD-1/anti-CTLA-4), and transcriptomic profiles were used for checkpoint dynamics analysis and clinical response association. (b) Dataset overview. Bar chart showing the number of paired patients (pre + post biopsies) per cohort and cancer type. n = 42 from GSE91061 (melanoma), n = 11 from Sade-Feldman2018/ GSE120575 (melanoma), n = 11 from Yost2019/ GSE123813 (BCC); total n = 64. (c) Meta-analysis mean fold-change (Z-score) per checkpoint gene across all datasets. Asterisks indicate genes reaching padj < 0.05. Genes are colored by functional category: inhibitory checkpoints (red), co-stimulatory molecules (teal), metabolic checkpoints (salmon), exhaustion markers (blue-grey). (d) Six-step analysis pipeline: data collection (4 cohorts, n = 64 paired) → pseudo-bulk aggregation and Z-score batch correction → paired DE analysis (Stouffer Z meta-analysis) → network rewiring (co-expression, hub shift) → ensemble model (AUC = 0.812, n = 38 genes) → clinical implication (combination therapy).

    Journal: Frontiers in Immunology

    Article Title: CheckDyn: a multi-cohort computational framework for profiling treatment-induced immune checkpoint dynamics and predicting adaptive resistance to immune checkpoint blockade

    doi: 10.3389/fimmu.2026.1847297

    Figure Lengend Snippet: Study overview: multi-cohort paired transcriptomics of checkpoint dynamics. (a) Study design schematic. Paired tumor biopsies were collected before and after ICB therapy (anti-PD-1 or anti-PD-1/anti-CTLA-4), and transcriptomic profiles were used for checkpoint dynamics analysis and clinical response association. (b) Dataset overview. Bar chart showing the number of paired patients (pre + post biopsies) per cohort and cancer type. n = 42 from GSE91061 (melanoma), n = 11 from Sade-Feldman2018/ GSE120575 (melanoma), n = 11 from Yost2019/ GSE123813 (BCC); total n = 64. (c) Meta-analysis mean fold-change (Z-score) per checkpoint gene across all datasets. Asterisks indicate genes reaching padj < 0.05. Genes are colored by functional category: inhibitory checkpoints (red), co-stimulatory molecules (teal), metabolic checkpoints (salmon), exhaustion markers (blue-grey). (d) Six-step analysis pipeline: data collection (4 cohorts, n = 64 paired) → pseudo-bulk aggregation and Z-score batch correction → paired DE analysis (Stouffer Z meta-analysis) → network rewiring (co-expression, hub shift) → ensemble model (AUC = 0.812, n = 38 genes) → clinical implication (combination therapy).

    Article Snippet: Across-dataset meta-analysis was performed using the Stouffer Z-score method, weighting each dataset by the square root of its sample size.

    Techniques: Transcriptomics, Functional Assay, Expressing

    Study overview: multi-cohort paired transcriptomics of checkpoint dynamics. (a) Study design schematic. Paired tumor biopsies were collected before and after ICB therapy (anti-PD-1 or anti-PD-1/anti-CTLA-4), and transcriptomic profiles were used for checkpoint dynamics analysis and clinical response association. (b) Dataset overview. Bar chart showing the number of paired patients (pre + post biopsies) per cohort and cancer type. n = 42 from GSE91061 (melanoma), n = 11 from Sade-Feldman2018/ GSE120575 (melanoma), n = 11 from Yost2019/ GSE123813 (BCC); total n = 64. (c) Meta-analysis mean fold-change (Z-score) per checkpoint gene across all datasets. Asterisks indicate genes reaching padj < 0.05. Genes are colored by functional category: inhibitory checkpoints (red), co-stimulatory molecules (teal), metabolic checkpoints (salmon), exhaustion markers (blue-grey). (d) Six-step analysis pipeline: data collection (4 cohorts, n = 64 paired) → pseudo-bulk aggregation and Z-score batch correction → paired DE analysis (Stouffer Z meta-analysis) → network rewiring (co-expression, hub shift) → ensemble model (AUC = 0.812, n = 38 genes) → clinical implication (combination therapy).

    Journal: Frontiers in Immunology

    Article Title: CheckDyn: a multi-cohort computational framework for profiling treatment-induced immune checkpoint dynamics and predicting adaptive resistance to immune checkpoint blockade

    doi: 10.3389/fimmu.2026.1847297

    Figure Lengend Snippet: Study overview: multi-cohort paired transcriptomics of checkpoint dynamics. (a) Study design schematic. Paired tumor biopsies were collected before and after ICB therapy (anti-PD-1 or anti-PD-1/anti-CTLA-4), and transcriptomic profiles were used for checkpoint dynamics analysis and clinical response association. (b) Dataset overview. Bar chart showing the number of paired patients (pre + post biopsies) per cohort and cancer type. n = 42 from GSE91061 (melanoma), n = 11 from Sade-Feldman2018/ GSE120575 (melanoma), n = 11 from Yost2019/ GSE123813 (BCC); total n = 64. (c) Meta-analysis mean fold-change (Z-score) per checkpoint gene across all datasets. Asterisks indicate genes reaching padj < 0.05. Genes are colored by functional category: inhibitory checkpoints (red), co-stimulatory molecules (teal), metabolic checkpoints (salmon), exhaustion markers (blue-grey). (d) Six-step analysis pipeline: data collection (4 cohorts, n = 64 paired) → pseudo-bulk aggregation and Z-score batch correction → paired DE analysis (Stouffer Z meta-analysis) → network rewiring (co-expression, hub shift) → ensemble model (AUC = 0.812, n = 38 genes) → clinical implication (combination therapy).

    Article Snippet: The CheckDyn pipeline integrates these datasets through pseudo-bulk aggregation, empirical Bayes batch correction, and Stouffer Z-score meta-analysis to quantify treatment-induced changes across a curated 38-gene checkpoint and exhaustion marker panel.

    Techniques: Transcriptomics, Functional Assay, Expressing

    Meta-analysis volcano and cross-dataset expression heatmap. (a) Meta-analysis volcano plot (3 cohorts). Genes reaching meta-padj < 0.05 (red): LAG3, PDCD1, TOX2 (top right). CD274, CD80 also approach significance. Dashed lines indicate significance thresholds. (b) Log 2 FC heatmap of significant genes per dataset. Color scale as in <xref ref-type=Figure 2a . Values are annotated per cell. LAG3 shows uniformly high log 2 FC across all three cohorts (0.49/0.76/0.74). " width="100%" height="100%">

    Journal: Frontiers in Immunology

    Article Title: CheckDyn: a multi-cohort computational framework for profiling treatment-induced immune checkpoint dynamics and predicting adaptive resistance to immune checkpoint blockade

    doi: 10.3389/fimmu.2026.1847297

    Figure Lengend Snippet: Meta-analysis volcano and cross-dataset expression heatmap. (a) Meta-analysis volcano plot (3 cohorts). Genes reaching meta-padj < 0.05 (red): LAG3, PDCD1, TOX2 (top right). CD274, CD80 also approach significance. Dashed lines indicate significance thresholds. (b) Log 2 FC heatmap of significant genes per dataset. Color scale as in Figure 2a . Values are annotated per cell. LAG3 shows uniformly high log 2 FC across all three cohorts (0.49/0.76/0.74).

    Article Snippet: The CheckDyn pipeline integrates these datasets through pseudo-bulk aggregation, empirical Bayes batch correction, and Stouffer Z-score meta-analysis to quantify treatment-induced changes across a curated 38-gene checkpoint and exhaustion marker panel.

    Techniques: Expressing