Statistically significant clusters for each contrast by the group analysis (n = 29). by Yuji Uchiyama (135480)

Summary map of all contacts with statistically significant SVM classifications. by Alexander P. Rockhill (6053618)

“…Yellow indicates an increase in time-frequency clusters during number trials versus inter-trial intervals while blue indicates a decrease in time-frequency clusters. …”

Multivariate and clustering analysis of metabolomic data. by Bhuripit Saraphol (20855573)

Significant clusters for gray matter volume loss per timepoint comparison. by Jesse D. de Groot (15401476)

Significant clusters for white matter volume loss per timepoint comparison. by Jesse D. de Groot (15401476)

ATGL-1 levels increase and lipid droplets decrease in response to <i>N. parisii</i> infection. by Hala Tamim El Jarkass (16625309)

Subjects:

Join-point regression analysis of the statistically significant linear increase in use of antidementia and antipsychotics during the observed time period. by Jelena Filimonovic (22305307)

Subjects:

Differentially expressed genes (DEGs) exhibiting both increased and decreased expression levels. by Liwen Wang (276995)

Significant clusters predicted for LSGs & <i>het</i>-like genes using Cluster Locator with Max Gap set to be 5, 1 and 0. by Zheng Wang (25883)

“…<p>Significant clusters predicted for LSGs & <i>het</i>-like genes using Cluster Locator with Max Gap set to be 5, 1 and 0.…”

Significant clusters (<i>P</i> < 0.05) predicted for LSGs using Cluster Locator with Max Gap set to be 5, 1 and 0. by Zheng Wang (25883)

“…<p>Significant clusters (<i>P</i> < 0.05) predicted for LSGs using Cluster Locator with Max Gap set to be 5, 1 and 0.…”

Homozygous microdeletions of SNPs in the rs58923657 non-risk haplotype result in significantly decreased <i>IKZF1</i> expression and increased proliferation in human LCLs. by Vincent U. Gant (9955199)

Phase 2 significant effects. by Wendy C. Crone (2262169)

Phase 1 significant effects. by Wendy C. Crone (2262169)

The combination of CUMS and smoke exposure significantly decreased the expression of pro-apoptosis factors and increase in anti-apoptosis factors when compared to stress or smoke group in the left lung. by Bai-Ping Liu (14164799)

Subjects:

A and B: Univariate LISA Cluster and Significance Map showing Spatial Clustering and Outliers of Complete CoC. by Mohd Usman (12705540)

Analysis of significantly down-regulated genes and comparison of cell clusters. by Jinming Wang (191356)

“…(C) Cell cluster comparison between <i>B. xinjiangensis</i> and ΔBxAP2-M2 using single-cell transcriptional sequencing (scRNA-seq).…”

Exploring Metalloproteome Remodeling in Calprotectin-Stressed Acinetobacter baumannii Using Chemoproteomics by Maximillian K. Osterberg (22514185)

“…A majority of the 2645 quantifiable Cys-containing peptides that show an increase in abundance-corrected Cys reactivity (150) are derived from known Zn-, Fe-, and Fe–S-cluster proteins, revealing a significant decrease in metal occupancy (undermetalation) across the proteome. …”

Exploring Metalloproteome Remodeling in Calprotectin-Stressed Acinetobacter baumannii Using Chemoproteomics by Maximillian K. Osterberg (22514185)

“…A majority of the 2645 quantifiable Cys-containing peptides that show an increase in abundance-corrected Cys reactivity (150) are derived from known Zn-, Fe-, and Fe–S-cluster proteins, revealing a significant decrease in metal occupancy (undermetalation) across the proteome. …”

Exploring Metalloproteome Remodeling in Calprotectin-Stressed Acinetobacter baumannii Using Chemoproteomics by Maximillian K. Osterberg (22514185)

“…A majority of the 2645 quantifiable Cys-containing peptides that show an increase in abundance-corrected Cys reactivity (150) are derived from known Zn-, Fe-, and Fe–S-cluster proteins, revealing a significant decrease in metal occupancy (undermetalation) across the proteome. …”

The optimal number of clusters identified using the GMM clustering algorithm. by Dinh K. Tang (20469082)