boxplot function in matlab software r2015a  (MathWorks Inc)

Journal: bioRxiv

Article Title: Hollow condensates emerge from gelation-induced spinodal decomposition

doi: 10.1101/2025.06.25.661497

Figure Lengend Snippet: ( a ) Droplet-like DPICs were initially formed by mixing 20 μM ATTO565-labeled p53 4M ΔTAD with 0.6 μM ATTO488-labeled Random DNA and incubating for 30 minutes at room temperature. Subsequently, Cy5-labeled p21 DNA was added at varying concentrations and incubated for an additional 120 minutes: (i) 0.15 μM; (ii) 0.225 μM; (iii) 0.3 μM; (iv) 0.45 μM; (v) 0.6 μM; (vi) 0.75 μM; (vii) 0.9 μM. Representative fluorescence images at incubation time t = 4-min and t = 120-min are shown. Independent in vitro droplet experiments were repeated three times (n = 3). ( b ) Boxplot of characteristic time constants τ 1 and τ 2 for p21 DNA concentrations ranging from 0.3 to 0.9 μM. N indicates the number of individual biomolecule-rich condensates analyzed under each condition. In box plots, the black line denotes the median, box edges represent the 25 th and 75 th percentiles, whiskers indicate the range excluding outliers, and outliers are shown as individual dots (•). ( c ) Phase diagram showing normalized fluorescence intensities of ATTO565-labeled p53 4M ΔTAD and ATTO488-labeled Random DNA at the center of condensates under increasing concentrations of p21 DNA (0.3, 0.45, 0.6, and 0.75 μM). Values are shown both before p21 DNA addition and at the end of Stage I. Control experiments in which Random DNA was used in place of p21 DNA are also included. Error bars indicate mean ± s.d. Green dashed lines mark the estimated binodal boundary, and purple dashed lines represent the spinodal boundary, as confirmed by our phase-field model (see – ).

Article Snippet: The function of “boxplot” in MATLAB software (R2015a, 64-bit, February 12, 2015) was used to plot the boxplots in , , and Supplementary Fig. 3.

Techniques: Labeling, Incubation, Fluorescence, In Vitro, Control

Journal: Nature Communications

Article Title: Environment geometry alters subiculum boundary vector cell receptive fields in adulthood and early development

doi: 10.1038/s41467-024-45098-1

Figure Lengend Snippet: A Venn diagrams showing the proportion of mEC cells classified as BVCs (blue), Border Cells (red), or both cell types (overlap region), for each age group. Coloured text above circles shows corresponding numerical percentages. Circles are scaled such that the square bounding box represents 100% of cells recorded in an age group. B Neuronal firing rate maps and best-fitting BVC model maps, for example BVCs and Border Cells. Each row shows example cell, columns of paired maps show data from different age groups (cells differ across age groups). Text adjacent to the neuronal firing rate map shows peak rate (top left, Hz) and Border Score (‘BS’; top right). Model map format as for Fig. . Top three rows show cells classified as both BVCs and Border Cells, middle two rows cells classified as BVCs but not Border Cells, bottom two rows cells classified as Border Cells but not BVCs. Boxplots showing distributions of Spatial Information ( C ), inter-trial stability ( D ) and intra-trial stability ( E ), for BVCs (blue boxes) and Border cells (red boxes) in each age group. Cells classified as both BVCs and Border Cells are included in both groups. Box shows IQR, circular target shows median, whiskers show limits of data excluding outliers. F Boxplots showing distributions of the BVC r (max) of BVCs (blue boxes; left y-axis) and Border Score of Border Cells (red boxes, right y-axis). Boxplot format as for ( C ). G Boxplots showing distributions of d tunings for BVCs (blue bars) and Border Cells (red bars), in each age group. Boxplot format as for ( C ). H Proportion of BVCs (blue bars) and Border Cells (red bars) with Φ oriented towards walls (±12°), in each age group. Error bars show 95% confidence interval for the proportion. Horizontal dashed line shows proportion expected, assuming a circularly uniform distribution of Φ .

Article Snippet: Boxplots were generated using the Matlab (The MathWorks Inc, USA) function ‘boxplot’.

Techniques: