County-level geographical septile distribution for the first 12 statistically significant factors with at least one statistically significant coefficient ranked by decreasing ΔIC. by Yanan Long (11784717)

Significant associations in GWAS. by Dai Nogimura (21445649)

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eQTL analysis of significant SNPs. by Dai Nogimura (21445649)

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Significant associations in the candidate gene approach. by Dai Nogimura (21445649)

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Significant disease phenotypes with LADA loci. by Margaret Sunitha Selvaraj (13994016)

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Number of patients with a significant increase or significant decrease between the baseline measurement (SCr-BL) and the creatinine measurement at emergency department presentation (SCr-ED). by M. S. A. Niemantsverdriet (11886431)

Seasonal spatial-temporal trend of NDVI in burned areas across Africa (2001–2020). Percentages (%) of increases or decreases (%) based on the Mann-Kendall test and statistically significant (<i>p</i> < 0.05) and non-significant (p > 0.05) values. by Oswaldo Maillard (20660661)

Suggestive significant associations in the candidate gene approach. by Dai Nogimura (21445649)

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Summary statistics from significant disease associations. by Margaret Sunitha Selvaraj (13994016)

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Nineteen SNPs with significant association (<i>P < </i>5 × 10⁻⁸) with risk on minJSW decrease in knee OA. by Mieke L. M. Bentvelzen (21594442)

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Significant rectangles are selected by using HC algorithm. by Shuting Liao (9524506)

Comparison of questionnaire scores among genotypes for the significant associations. by Dai Nogimura (21445649)

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QTLs identified and their association with the KASP Markers based on significant difference by Kruskal-Wallis test. by Harpreet Singh (677440)

Full list of proteins significantly enriched by BioID2 labelling. by Jan Pyrih (229124)

“…Columns D to G: statistically significant enrichment of a given protein against other bait protein datasets. “-”demarks when enrichment could not be calculated (<i>e</i>.…”

Significance analysis data. by Lei Zhu (16642)

“…The results indicate that: (1) The manifestation of mining pressure in gangue backfill mining is influenced by factors such as mining height and backfill collapse ratio; (2) Under the support of coal gangue, the concentrated stress in the coal seam significantly decreases, forming an arched shape according to the mining stages; (3) The range of plastic failure in the coal seam remains relatively stable under gangue backfill mining, with the plastic zone of the roof plate exhibiting a strip-like distribution; (4) Both range analysis and variance analysis revealed that the sensitivity ranking is backfill collapse ratio > mining height > elastic modulus. …”

<i>BZP4</i> expression differs significantly between genotypes. by Thomas J. C. Sauters (17382864)

“…</b> A hierarchically clustered heatmap of genes that strongly correlate with <i>BZP4</i> expression and are differentially expressed based on the <i>BZP4</i> allele in amoeba treated samples. …”

Details of significantly differentially abundant metabolites (<i>PPP1CC</i>-SSKO vs control). by Jiahong Sun (6497603)

Posterior, mid-posterior, central, and mid-anterior corpus callosal volume significantly decreased with increasing risk of environmental lead exposure. by Andrew T. Marshall (10159199)

Bacterial Lineage Cladograms with Significantly Different Representation in Infected and Uninfected Groups. by Xi-Meng Sun (17721428)

Descriptive statistics based on type of therapy and time of assessment. by Nina Brkić-Jovanović (18886883)

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