Curated Collections

By plottie

Collection Links

Representative FACS plots and quantifications of p-SYK, p-ERK, and p-AKT expression in indicated subsets.
Venn diagram of overlapping genes between (upper left) genes enriched in A375 control cells versusALDH1A3KO cells mapped from total histone H3 acetylation and (upper right) MPD002 control cells versus ALDH1A3 knockdown cells mapped from histone H3K23 acetylation.pvalues by Fisher’s exact test. Transcription factor binding motif over-representation analysis of the Venn diagram overlapping genes (lower panel) showed significant enrichment of AP-2 binding motif, with enrichment score by g:Profiler (e111_eg58_p18_30541362) with g:SCS multiple testing correction method applying statistical significance threshold of 0.05.64
Scatterplot of activity difference in days 1-2 (top) and in days 2-3 (bottom).
(Left) SM average chain length and unsaturation show the differences in SM features remodeling in M. mycoides (filled circles) and Syn3B (outlined circles). Mean ± standard deviation, n= 3. (Right) SM average features plotted against each other for RBL-derived GPMVs. n= 4 ± standard deviation, data adopted from Levental et al. n refers to the number of biological replicates in all samples.

Multiple Panel Plot

Multiple Panel Plots (faceted plots or small multiples) enable powerful multi-dimensional data visualization by displaying related graphs in organized grids. This extensive collection showcases publication-quality examples from diverse scientific fields, demonstrating effective data comparison across conditions, time points, or experimental groups. Perfect for researchers analyzing complex datasets, dose-response curves, time-series data, or multi-condition experiments. Master techniques for creating consistent, publication-ready multi-panel figures using ggplot2 facets, matplotlib subplots, and specialized tools like cowplot and patchwork for professional scientific data visualization.

295 plotsUpdated 7 days ago
Schematic overview of the 16 deletion constructs. Each segment is replaced by an in-frame SbfI restriction site encoding Pro-Ala-Gly.
Schematic showing delivery of PSD95-FingR-GFP, Gephyrin-FingR-tdTom, and smFP into pyramidal neurons by in utero electroporation to simultaneously label excitatory (green) and inhibitory synapses (red) as well as the entire neuron (blue).
Schematics illustrating consequences of apical cell constriction or expansion on tissue shape in the absence or presence of oriented cell intercalation.
The flight chamber with the microphone array system measures the 3D direction and beamwidth of pulses emitted by bats during moth-capture flight. The microphone array consists of 31-channel microphones. Seventeen microphones are arranged in a U-shape on the X-Y plane 1.2 m from the floor (blue frame). Seven microphones are vertically placed on the Z-X plane (red frame) and combined with 12-channel microphones in an O-shape on the Y-Z plane at a 2-m distance from the front wall (green frame). The microphones are spaced at 0.5-m intervals on the x axis, 0.8-m intervals on the y axis, and 0.45-m intervals on the z axis.

Flowchart

Flowcharts provide essential visual frameworks for illustrating scientific processes, experimental protocols, and analytical pipelines. This comprehensive collection features publication-quality flowchart examples from bioinformatics workflows, clinical algorithms, and laboratory procedures. Invaluable for researchers documenting computational pipelines, diagnostic pathways, or standard operating procedures. Learn to create clear, professional flowcharts following scientific standards using draw.io, Lucidchart, mermaid diagrams, and specialized workflow visualization tools for reproducible research documentation.

243 plotsUpdated 7 days ago
The ratio of c-Fos+/dTomato+co-expressing cells to the total Gad67+cells were determined in the lateral hypothalamus. All cell counts were performed using the ImageJ cell counter. Data are presented as mean (n= 5) standard deviation. Significant differences were determined via the unpaired t test (two-tailed).pvalue*p< 0.05 and**p< 0.01. Abbreviations: LHA, lateral hypothalamic area; CNO, clozapine N-oxide; MRI, magnetic resonance imaging; AAV, adeno-associated virus; and RFP, red fluorescent protein.
The lactate content in HRMECs in response to VEGF stimulation (mean ± SEM; n = 4 samples per group; * P < 0.05, *** P < 0.001, one-way ANOVA, Bonferroni post hoc test).
Quantification of the percentage of indicated B. thailandensis strain colocalizing with Ubiquitin, as determined by microscopy at 6 h p.i.
Statistic comparison of the width of lumen of PTs between in WT/WT mice (n = 7) and NUMB R632H /NUMB R632H mice (n = 6).

Bar Plot with Error Bars

Bar Plots with Error Bars are fundamental for presenting quantitative comparisons with statistical uncertainty in scientific research. This extensive collection showcases publication-quality examples from molecular biology, clinical trials, and experimental psychology. Critical for researchers displaying means with confidence intervals, standard errors, or standard deviations across experimental conditions. Master proper error bar implementation, statistical annotation, and visual design using ggplot2, matplotlib, GraphPad Prism, and specialized tools for creating accurate, reproducible scientific figures.

126 plotsUpdated 7 days ago
Notch transcriptional activity visualized with a Notch responsive element reporter (white). Notch in Rh1G69D-expressing cells (GFP+) compared with wild-type cells (GFP−). Error bars, 95% confidence intervals.p 0.0001. Scale bars, 20 μm.
Phasmid egg morphospace showing egg length over width and height over width. These aspect ratios explain most of the variation in egg shape (Figure S1). Black lines between points represent underlying phylogenetic relationships. Egg silhouettes are represented in dorsal (left) and side (right) view. Bottom right inset shows the drawing of a phasmid egg (Eurycnema osiris). Cap, capitulum; Cas, capitulum stalk; Op, operculum; Ca, egg capsule; Mpp, micropylar plate; Mpc, micropylar cup; Ml, median line; L, egg length; W, egg width; H, egg height. Colors correspond to oviposition mode.
NTS and TS cleavage of the 20- and 16-bp substrates measured for WT and RuvC lid mutants. Colored circles represent individual replicates. Black lines define the mean standard error of the mean (SEM).
Relative fold change of the GSSG/GSH ratio in relative units (RUs) in neurons that were exposed to 50 M glutamate for 4 h (n= 5 per group).

Scatter Plot

Scatter Plots form the foundation of exploratory data analysis across all scientific disciplines, revealing patterns, correlations, and outliers. This extensive collection showcases diverse scatter plot applications from basic correlations to advanced techniques like UMAP dimensionality reduction and PCA visualization. Essential for researchers in genomics, drug discovery, and quantitative biology analyzing high-dimensional data, clustering results, or multivariate relationships. Discover best practices for creating publication-quality scatter plots with proper scaling, coloring, and annotation using ggplot2, matplotlib, seaborn, and specialized tools for scientific data visualization.

123 plotsUpdated 7 days ago
An example of the trajectories of original and simulated pure pursuit flights (top view). The circles indicate the animals location when the bat started to react to the update of target information 120 ms after each pulse emission. These trajectories indicated that the bat followed a clear, short-cut course. Top and side views of trajectories in all sessions are available in a repository (see data and code availability in STAR Methods).
Data from young and old ants were pooled, and results from the three alarm pheromone stimuli were compared. Data points are slightly jittered. For (B) and (C), we used the extra sum-of-squares F test on same versus different curves, and vertical gray bars show the time window when the stimulus was added to the arena. SeeData S1for behavioral data. SeeTable S1for statistical analysis details. Data points show mean SEM. Ribbons show 95% CI of the curves. ns,p> 0.05.
Original (pale) and smoothed (dark) excitation spectra of1(f, h, j) and2(g, i, k; both at 3 nM) in DPPC (f, g), DSPC (h, i), or DBPC LUVs (j, k) upon cooling.
The FT-IR spectrum of TAPB-TA@KB/S, TAPB-TA polymer film and the monomers, respectively.

Line Plot

Line Plots excel at showing trends, time-series data, and continuous relationships across all scientific disciplines. This extensive collection features diverse line plot applications from growth curves, reaction kinetics, to climate data visualization. Essential for researchers tracking changes over time, comparing multiple series, or showing dose-response relationships. Discover techniques for creating clear, publication-quality line plots with proper scaling, annotations, and multi-series comparisons using ggplot2, matplotlib, and specialized time-series visualization tools.

122 plotsUpdated 7 days ago
The effects of mutations in the ligand-binding pocket of TAAR1 in response to LSD as determined using the GloSensor assay. The heatmap is colored according to the ΔpEC50 value (ΔpEC50 = pEC50 of mutant − pEC50 of the wild type) and Emax (the relative percentage compared with the wild type). Data are from three independent experiments (n= 3). ND, signal not detectable.
E. coli BW25113 strains expressing HigBAC, CmdTAC, or the hybrid CmdTA-HigC TAC operon composed of CmdTA toxin-antitoxin unit and HigC chaperone were challenged with 10-fold serial dilutions of BASEL23 and common lab coliphages, including the virescape_1 escape mutant variant. the results of the full screen are shown
Heatmap of the differentially expressed genes between the human adipose stem cell (hASC) and the pre-adipocyte (hPreA) populations across depots, based on (C).
Heatmap of top enriched gene set in each cluster of p53 WT vs. p53 KO cells at 24 h post transplantation, demonstrating increased cell death-related genes in clusters 3, 5, and 6 and survival-related genes in clusters 2 and 4. Red font indicates survival-related genes.

Heatmap

Heatmaps excel at visualizing matrix data patterns in genomics, proteomics, and multivariate analysis across scientific fields. This extensive collection features publication-quality heatmap examples from gene expression profiling, correlation matrices, and spatial data analysis. Critical for researchers performing clustering analysis, differential expression studies, or multi-condition comparisons. Master advanced heatmap techniques including hierarchical clustering, annotation tracks, and color scale optimization using R ComplexHeatmap, Python seaborn, and specialized bioinformatics visualization tools.

101 plotsUpdated 7 days ago
MS2 of 13C-putrescine tracing in E. coli demonstrating putrescine incorporation into diacetylspermidine. Data are mean SEM;p< 0.05;p< 0.01;p< 0.001;p< 0.0001. See also Figure S2.
The top 15 terminologies of biological process (BP) in gene ontology (GO) analysis based on PTVs linked to liver-related biomarkers.
Medium-term cost-neutral price thresholds for novel rifampin-susceptible regimens in India under the societal perspective. Coloured bars show the variation in the price threshold when a single characteristic is varied from its standard-of-care value to its optimal TRP value. The values that the non-varying characteristics take on differ between the three sections of each panel; the bottom sections of both panels (all but one characteristic set to standard of care) show thresholds when all non-varying characteristics are fixed at their standard-of-care values (vertical dashed line), the middle sections of each panel (all but one characteristic set to minimal TRP) show results when all non-varying characteristics are fixed at their minimal target values from the TRPs (table 2), and the top sections of each panel (all but one characteristic set to optimal TRP) show results when all non-varying characteristics are fixed at their optimal values from the TRPs. Colours indicate which characteristic is being varied, and text labels indicate the values of each characteristic (left of the bars, standard-of-care values for each characteristic; right of the bars, TRP-optimal values for each characteristic). Bars are ordered vertically by the effect each characteristic has on the threshold (the vertical distance between each bar is equal and not meaningful). TRP=Target Regimen Profile. UI=uncertainty interval.
Distance violations versus the size of the ensemble for the PDB ID7M5T.

Bar Plot

Bar Plots remain fundamental for comparing categorical data across scientific disciplines, from molecular biology to clinical research. This comprehensive collection features publication-quality bar plot examples demonstrating effective data presentation, error bar usage, and statistical annotation. Essential for researchers presenting gene expression levels, treatment comparisons, or survey results. Master best practices for creating clear, accurate bar plots with proper baseline, spacing, and statistical indicators using ggplot2, matplotlib, GraphPad Prism, and other scientific plotting tools.

90 plotsUpdated 7 days ago
Quantifications for the average peak amplitudes of Arp3 when cell expresses mCherry-Arp3 or co-expresses mCherry-Arp3 with formin constructs. Sample sets for (J) and (K): single expression of mCherry-Arp3: 15 cells. Co-expression of mCherry-Arp3 with the following: FMNL1-GFP: 22 cells; GFP-FMNL1CT: 16 cells; GFP-CA-FMNL1: 9 cells; GFP-mini-FMNL1-T126D (inactive mutant): 16 cells; GFP-mini-FMNL1-V281E (active mutant): 14 cells. Statistical significance:**p< 0.0001; ns, not significant;**p< 0.012–0.0055, 1-way ANOVA, Dunnett’s multiple comparison test. Error bars represent mean ± SEM.
Percentage of TCR sharing between non-gut tissue pairs (kidney, pancreas, lung) and gut-non-gut tissue pairs (LPL with kidney, pancreas, or lung), relative to the split sample TCR sharing rates. Box-and-whisker plots with mean and quartiles.
Proportion of endothelial or perivascular cells generated at day 14 following treatment with FGF2, C2-58-2X_mb7, C6-79C_mb7, mb7 alone, or mb7 in combination with FGF2. Error bars represent SEM from 3 independent biological repeats.
Sequencing data were collated from the American Gut Project and prior analyses of the AGEhIV cohort and were processed in identical fashion [ 46 , 48 , 52 ] using dada2 [ 56 ]. For both datasets, Canberra beta-diversity matrices were calculated, and PERMANOVA tests were performed to quantify significance and effect sizes of ecological distances between cases and controls for each disease. Sample sizes are shown in parentheses encompassing balanced cohorts of cases and controls matched for confounding variables displayed at top left. For HIV cohorts, PERMANOVA statistics were calculated on five total sample groups from two studies [ 46 , 52 ] including the following: men who have sex with men ( n = 76) [ 46 ], females ( n = 38) [ 46 ], men who have sex with women ( n = 34) [ 46 ], combined females and males (irrespective of sexual behavior (148) [ 46 ], and a separate cohort of men who have sex with men ( n = 102) [ 52 ]

Box Plot

Box Plots (box-and-whisker plots) are statistical workhorses for comparing distributions across groups in experimental research. This comprehensive collection features publication-quality box plot examples from clinical trials, biological experiments, and behavioral studies. Essential for researchers presenting median comparisons, quartile ranges, and outlier identification across multiple conditions. Learn to create informative box plots with statistical annotations, notches, and violin plot overlays using ggplot2, matplotlib, GraphPad Prism, and specialized statistical visualization tools.

77 plotsUpdated 7 days ago
Distance between apical or basal side of CD8-GFP-labeled clones of cells and morphogenetic furrow over time. Clones move into and out of morphogenetic furrow. Mean and SEM are shown.n= 5 clones in 5 eye discs. See alsoFigure S4andVideos S7andS8.
PPC between V1 LFPs and V1 single units (SU) (n= 311) or V4 SUs (n= 397).
One-dimensional configuration coordinate diagram for charge transitions between VSe(2)2+ and VSe(2)+. Solid circles are data points obtained by DFT calculations and used for fitting, while hollow circles are discarded for fitting due to charge delocalization (see section VSe2+leftrightarrowVSe+ ofsupplemental information). Solid lines represent best fits to the data.
Vaginal levels of IL-17A over the course of the study between colonization-resistant and permissive women. Shaded area represents time during metronidazole treatment which was not included in analyses. p values determined with linear mixed models including all time points during LACTIN-V administration ( n = 32). Data points and error bars are mean and 95% confidence intervals, respectively

Line Plot with Error Bars

For a more rigorous approach to time-series and experimental data, the Line Plot with Error Bars is an invaluable tool. It enhances the standard line plot by adding error bars to each data point, illustrating the uncertainty or variability at each measurement interval. This is particularly useful in scientific fields for representing confidence intervals or standard errors of a mean over time. By visualizing both the trend and its statistical precision, you can make more informed judgments about the data's reliability and the significance of observed changes. This chart is essential for presenting experimental results transparently, enabling a deeper and more accurate interpretation of trends.

54 plotsUpdated 29 days ago
The ancestral state reconstruction used stochastic character mapping and a transition matrix (inset) estimated by maximum likelihood. Scaled egg pictures in dorsal view correspond to the species listed inTable S1. Dropped or flicked eggs are represented by a green oval, buried eggs by a brown triangle, and glued eggs by a yellow droplet.
Summary of associations of HbA1c and its signal classification in ferritin, liver iron content (MRI), and liver steatosis (meta-analysis). HbA1c, hemoglobin A1c; Glycemic, probability of the variant in glycemic class, included fasting insulin, 2-hour glucose, and fasting glucose; Reticulocyte, probability of the variant in reticulocyte class, included reticulocyte count, reticulocyte fraction of red cells, immature fraction of reticulocytes, high light scatter reticulocyte count, and high light scatter reticulocyte percentage of red cells; Mature RBC, probability of the variant in mature red blood cell class, included red blood cell count, mean corpuscular volume, hematocrit, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, hemoglobin concentration, and red cell distribution width; Iron, probability of the variant in iron class, included ferritin, transferrin, serum iron, and transferrin saturation; OR, odds ratio; 95% CI, 95% confidence interval
Inset showing a detailed view of region b from panel a . This region has connected adrenergic I and adrenergic II programs. In this inset, nodes have been colored by dataset, rather than community (as in panel a ).
Phylogenetic representation of a single public SARS-CoV-2-specific clonotype. All mAbs in the clonotype use the IgG1 isotype except for a single IgA1 clone (indicated by text and an unfilled marker).

Network

Network Plots reveal complex relationships in biological systems, from molecular interactions to ecological food webs. This comprehensive collection features sophisticated network visualizations from protein-protein interactions, gene regulatory networks, and metabolic pathways. Critical for systems biology researchers, network pharmacologists, and ecological modelers. Master advanced network visualization techniques including force-directed layouts, community detection, and interactive exploration using Cytoscape, Gephi, R igraph, and specialized biological network analysis tools.

50 plotsUpdated 7 days ago
Fig. 3 . Cell death at single-cell resolution.
A UMAP projection showing 15 neutrophil subpopulations.
Left: spatial RNA velocity streamlines visualization of the directional flows. Right: RNA velocity PAGA graph predicting the developmental trajectory of the ectoplacental cone and P-TGCs in section E8.5 S1. Bins are colored by cluster identity, as in a .
DDRtree clustering of the Mono/Macro cells with DEGs selected using unsupervised methods implemented in monocle R package.

UMAP Plot

A UMAP (Uniform Manifold Approximation and Projection) Plot is a cutting-edge technique for dimensionality reduction and data visualization. It is particularly powerful for exploring the structure of large, high-dimensional datasets. UMAP excels at preserving both the local and global structure of the data in a low-dimensional space (typically 2D or 3D). This makes it invaluable in fields like bioinformatics for visualizing single-cell RNA-sequencing data, or in machine learning for understanding complex feature spaces. Use a UMAP plot to uncover hidden clusters, relationships, and manifold structures that other methods might miss, providing profound insights into complex data.

47 plotsUpdated 29 days ago
Time line of the acute AAV-mediated deletion of the miR-379-410 cluster in excitatory neurons of the hippocampus and behavioral testing.
Schematic illustration of PA-N differentiation conditions with PD17 (0.5 M) added at two subsequent time points following PDA83 (PA) treatment.
Experimental setup for local activation. The numbers indicated in the gel refer to the areas of which the absorbance or fluorescence intensity values are measured. Experimental data for areas 15 are reported in the following Figures.
Schematic representation of the experimental protocol (n= 7 mice). ΔF/F0was measured for putative neurons in vS1 while mice were presented with a metallic pole in six different positions along their anterior-posterior axis, both before (pre-training session, light orange) and after training on the pole localization task (post-training, brown).

Study Design

Study Design Diagrams provide essential visual roadmaps for research methodology, crucial for clinical trials, experimental protocols, and systematic reviews. This collection features clear, professional study design visualizations from high-impact publications, including CONSORT diagrams, experimental workflows, and sampling strategies. Invaluable for researchers planning RCTs, cohort studies, or complex experimental designs. Learn to create transparent, reproducible study design figures using specialized tools like draw.io, Lucidchart, and R packages for CONSORT flow diagrams that meet publication standards.

43 plotsUpdated 7 days ago
Volcano plots displaying proteins identified by TAP-MS of 2SC-INTS13ΔC over GFP control under normal growth conditions or glucose starvation. Significantly enriched proteins (log2[INTS13ΔC/GFP] > 2,p< 0.05) are colored (black: Integrator subunits, orange: TFs, green: chromatin remodelers, pink: RNAP2, red: elongation factors, blue: histone modifiers). TFs that are not significantly bound but significant in another condition are labeled in gray.
Volcano plot of proteins identified in P300 proximity labeling experiments in gastruloids.
Volcano plots of the differential expression analyses. Blood Treg cells are contrasted with the means of all other Treg cell samples, followed by pairwise contrasts of the remaining three tissue groups.
As in (A) and (B) but for MCF10a GCN2 compared to WT (E) (seeFigure S9A;Table S2). Statistical tests as in (A) and (B). SeeFigures S9andS6G;Tables S2andS3; andData S1.

Volcano Plot

Volcano Plots are indispensable for visualizing differential expression in omics studies, combining fold change with statistical significance. This collection presents outstanding volcano plot examples from RNA-seq, proteomics, and metabolomics publications. Essential for researchers identifying differentially expressed genes, proteins, or metabolites in high-throughput experiments. Explore advanced techniques for creating publication-quality volcano plots with proper thresholds, labeling, and color coding using R packages like EnhancedVolcano, ggplot2, and specialized bioinformatics tools.

35 plotsUpdated 7 days ago
Schematic illustration highlights that hypoblast emerges upon release from PDA83 in both 2D adherent differentiation and during blastoid formation. Cells encounter an FGF-responsive window that underpins hypoblast specification in both stem cell models and in human embryos.
Schematic diagram of adsorption and loading of Ag nanoparticles (NPs) by redox-active COF. Reproduced with permission.[72]Copyright 2020, American Chemical Society.
Sample rotation changes the in-plane momenta of each excitation field and determines the nonlinearity that arrives at the detector.
Design of the SIINFEKL epitope saturation mutagenesis library. Each position was substituted to each of the 19 alternative amino acids. In addition to the epitope, the two amino acids that were N terminal and C terminal to the epitope were examined. Each mutant epitope was expressed as 56-aa peptide tiles, introduced into H2-K b + G 5 -target cells and screened using OT-I TCR + SrtA-Jurkats using TCR-MAP.

Workflow Diagram

Workflow Diagrams document complex research processes, computational pipelines, and experimental procedures with clarity and precision. This collection showcases professional workflow visualizations from bioinformatics pipelines, clinical protocols, and laboratory methods. Essential for researchers ensuring reproducibility, training personnel, or documenting standard procedures. Discover best practices for creating clear, detailed workflow diagrams using specialized tools like Nextflow, WDL visualization, draw.io, and scientific workflow management systems.

35 plotsUpdated 7 days ago
Distributions of NDI between self-reported Black/African American and non-Hispanic White participants.
The electric field of a BSV pulse: the mean value is constantly zero, while the variance oscillates at twice the carrier frequency.
Posterior estimated velocity plot inferred for cultured human fibroblasts 32 using the original SVI mode of VeloCycle and either all genes (left) or random gene subsets (50% of total genes; right).
DFT C-O stretching wavenumber as a function of the Cu-Cu coordination number, decreasing from orange ( N Cu-Cu = 4-5) to dark brown ( N Cu-Cu = 7-8).

Density Plot

A Density Plot provides a beautiful and intuitive way to visualize the distribution of a continuous variable. It works by smoothing out the data points to create a continuous curve, offering a clearer representation of the underlying probability distribution than a traditional histogram. This plot is excellent for exploring the shape of your data, identifying peaks (modes), and understanding where the data points are concentrated. Whether you're analyzing income distribution, measurement data, or any continuous dataset, the density plot helps reveal patterns that might be missed with other charts. It is a key tool for exploratory data analysis and statistical modeling.

35 plotsUpdated 29 days ago
Measurement of mitochondrial size and roundness in heart from transmission electron microscopy of skeletal muscle and heart from adult fish (n= 3 males per genotype). Unpaired t test.
Ratio of Epi/PrE cells per embryo in treated embryos.
Total number of MNCs in the CNS.
Maximum clinical score.

Violin Plot

Violin Plots combine distribution visualization with statistical summary, superior to box plots for revealing data shape and density. This collection showcases elegant violin plot examples from single-cell genomics, clinical biomarkers, and population studies. Perfect for researchers comparing complex distributions, multimodal data, or large sample datasets. Master techniques for creating publication-quality violin plots with statistical overlays, split violins, and hybrid visualizations using ggplot2, seaborn, and specialized tools for advanced distribution analysis.

33 plotsUpdated 7 days ago
Diagram of the proposed mode of action for BSK proteins and YDA in the context of IDA perception during floral organ abscission. BSK proteins, as interactors of HAE/HSL2 as well as of YDA, could scaffold their assembly and allow activation of YDA by the plasma membrane receptors. Once activated, YDA would trigger the MAPK phosphorylation cascade and induce abscission. Protein shapes were based on their respective AlphaFold database models (excluding unstructured domains), except for the extracellular domains of HAE/HSL2, SERK, and the IDA structure that were extracted from PDB:5IYX.
Targeting metabolic regulation in hepatic immune and stromal cells offers novel opportunities for treating liver fibrosis. Endoplasmic reticulum (ER) stress, glycolysis, andde novolipogenesis are regulated in a similar fashion in macrophages, T cells, and activated HSCs (aHSCs) and, therefore, could target the activation of all three lineages (red outline). Activation of nuclear receptor signaling through peroxisome proliferator-activated receptor (PPAR), liver X receptor (LXR), or farnesoid X receptor (FXR) elicits anti-inflammatory and anti-fibrotic effects on macrophages and HSCs (blue outline), though effects on hepatic lymphoid populations have not yet been described. Furthermore, autophagy and ferroptosis have discrete roles in macrophage and stellate cell activation. Although autophagy is anti-inflammatory in macrophages, it is critically involved in the activation of HSCs. Similarly, ferroptosis has anti-fibrotic effects and limits HSC activation, while overall its net effect is understood to be more proinflammatory. In addition, at least in metabolic-dysfunction-associated steatohepatitis, targeting macrophage scavenging receptor 1 (MSR1) may limit lipid-induced macrophage inflammation. Not least, considering the complex interplay of metabolic pathways, cell-targeted drug delivery may help in reducing off-target effects. ACC, acetyl-CoA carboxylase; CCL2, C-C-motif ligand 2; ER, endoplasmic reticulum; FASN, fatty acid synthetase; FFA, free fatty acid; IL, interleukin; IRE1alpha, inositol-requiring enzyme 1 alpha; MSR1, macrophage scavenging receptor 1; OCA, obeticholic acid; PKM2, pyruvate kinase M2; PDGF, platelet-derived growth factor; PPAR, peroxisome proliferator-activated receptor; ROS, reactive oxygen species; SCD-1, stearoyl-CoA desaturase; TNF-alpha, tumor necrosis factor alpha. Created withBioRender.com.
2D representation of GAT-1 organized by 12 TM domains and linking or terminal chains. Only missense and in-frame variants are highlighted.
Schematic showing the working model of how mannose is crucial for mesoderm specification. Red boxes denote the inhibitors that block the production or recycling of mannose.

Pathway Diagram

Pathway Diagrams are fundamental visualization tools for illustrating biological pathways, metabolic networks, and signaling cascades in life sciences research. This curated collection features publication-quality pathway diagram examples from leading journals, showcasing KEGG pathways, gene regulatory networks, protein-protein interactions, and cellular signaling mechanisms. Perfect for molecular biologists, biochemists, and systems biology researchers creating figures for scientific publications. Find inspiration for visualizing complex biological processes, drug targets, disease mechanisms, and multi-omics data integration using tools like Cytoscape, PathVisio, and BioRender.

26 plotsUpdated 7 days ago
RT-qPCR-measured NCSC gene expression change in A375 and MPD002 in response to pyruvate dehydrogenase (PDH) activity change induced by PDH inhibitors (PDHis) CPI-613 (upper) and AC-148 (lower).*p< 0.05;**p< 0.01;***p< 0.001; one-way ANOVA with Sidaks correction.
CSF concentrations are significantly higher than serum in individuals with AGS (p= 0.005, two-tailed paired Wilcoxon test). Serum IFN-α concentrations are significantly higher in serum than CSF in individuals with SLE (p< 0.0001, two-tailed paired Wilcoxon test). Data from 133 blood-CSF pairs.
Cavalier’s probe for volume at day 7 post grafting (B).
Depicts total sleep over 24 h for individuals from (F) and (G) using increasing periods for the minimum sleep bout threshold. Two-way repeated measures ANOVA finds a significant genotype-by-threshold interaction (F(30,2244)= 6.142,p< 0.0001,n= 62–64 flies/group).

Paired Dot Plot

Paired Dot Plots excel at visualizing before-and-after comparisons, treatment effects, and matched sample analyses in biomedical research. This collection features publication-ready paired dot plot examples demonstrating statistical comparisons, clinical trial results, and experimental interventions. Perfect for researchers presenting paired t-test results, repeated measures data, or matched case-control studies. Learn effective techniques for showing individual data points, connecting lines, and statistical significance using ggplot2 paired plots, GraphPad Prism, and Python seaborn for creating transparent, reproducible scientific figures.

24 plotsUpdated 7 days ago
Summary of shape change and displacement of cells progressing through the morphogenetic furrow. Cells entering MF constrict both apically and basally and undergo intercalations at both apical and basal sides forming new junctions parallel to MF. Cells exiting the MF expand their apical area and undergo intercalation, forming new junctions perpendicular to MF. Basal area of non-photoreceptor cells (depicted here) expands. Within MF, apical cell side flows toward anterior. Cells entering and exiting MF form protrusions oriented preferentially toward the posterior that enable basal cell displacement toward posterior, leading to tilting of cells. See alsoFigure S7andVideo S13.
Proposed mechanism for ecCFAS showing the role of the Tyr137 and Tyr350 residues.
Schematic illustration of Mps1 functions at the kinetochore. Ndc80 acts as the main kinetochore receptor for Mps1. Mps1 promotes mitotic checkpoint complex assembly as well as establishment of bi-oriented end-on attachments.
A new landmark (blue) deflects the bump onto a new trajectory (k).

Hypothesis Illustration

Hypothesis Illustrations transform complex scientific theories into clear visual narratives, essential for grant proposals, review articles, and research presentations. This curated collection showcases conceptual diagrams, theoretical frameworks, and mechanistic models from top-tier publications. Ideal for researchers communicating novel hypotheses, experimental designs, or theoretical models in fields ranging from neuroscience to ecology. Explore effective visual storytelling techniques using Adobe Illustrator, BioRender, PowerPoint, and specialized scientific illustration tools to create compelling hypothesis visualizations that enhance research communication.

22 plotsUpdated 7 days ago
log-response ratio of community composition shift (LRR shift). The global response (all data) is shown on the first row of each panel and is separated by factors in the following rows. The numbers in parentheses indicate the number of comparisons. For each category the dot represents the marginal mean computed from the model; dot size is proportional to number of studies included. The larger bar shows the 95% confidence interval and the thinner bar represents the 99% confidence interval.
A multiple linear regression (MLR) model summarized the relationship between the number of photostimulated stimulus-coding and non-coding neurons and perceptual bias. Marker points shown the estimated coefficients with error bars indicating the 95% confidence intervals.
Country-specific linear regression models predicting perceived fairness of actual carbon footprint inequality. Sample sizes: Denmark ( N = 931), India ( N = 949), Nigeria ( N = 956) and the USA ( N = 920).
Crude and adjusted risk difference (red circle represents mean risk difference and blue error bars represent 95% CI of the risk difference) in clinical pregnancy rates between the iDAScore and the control groups (a negative risk difference indicates lower clinical pregnancy rate in the iDAScore group) per intention-to-treat (ITT) analysis (n = 1,066) and PP analysis (n = 1,002).

Forest Plot

Forest Plots are the gold standard for meta-analysis visualization, displaying effect sizes and confidence intervals across multiple studies. This collection showcases exemplary forest plots from systematic reviews, clinical meta-analyses, and evidence synthesis publications. Critical for researchers conducting Cochrane reviews, clinical guidelines, or comparative effectiveness research. Learn to create professional forest plots showing pooled effects, heterogeneity statistics, and subgroup analyses using specialized R packages like meta, metafor, and forestplot for publication-ready meta-analysis figures.

20 plotsUpdated 7 days ago
Egg width as a function of the width of the adult female ninth tergite (i.e., where the egg is released). Phylogenetic least-square regressions are shown and correspond to the analyses in Table S3. Dashed lines represent the equality line.
Relationship between the image-based adiposcore in (D) versus the transcriptomic-based “mature adipocyte score” from the same donor. Samples are grouped by depots (SC, yellow; PR, brown) and donors. Spearman correlation and adjusted R2 of y ∼ log(x + 1) (plotted orange line with 95% confidence interval) values are indicated.
Plot of mean diffusion distance versus time of travel within the channel. The inset graphically shows how diffusion distances were determined. The diffusion distance corresponds to the half of the full-width half maximum (FWHM) of the Gaussian distributions at each measurement point. The width at timepoint zero was used for normalization. Data points (mean) are from three repeats; error bars indicate standard deviations. The orange line shows the fit according to Eq. 1 . The extracted average R H of TDP-43 nanoclusters is given as an inset (mean ± standard deviation).
Plots showing the correlation between average log 2 (fold change) of gRNA targeting indicated genes in the following cells and conditions: Pik3ca H1047R/wt cells ( y axis) versus WT cells ( x axis) in control (CTL) condition (the panels indicate gene sets of PI3K pathway genes (top) and mTOR pathway genes (bottom)). In c – e , the yellow and green areas of each graph indicate the higher absolute log 2 (fold change) in x -axis or y -axis condition, respectively. Linear regression (black) with slope and coefficient of determination R 2 . Identity line, orange. The error bars indicate the s.d. of n = 2–3 screen replicates.

Regression Plot

Regression Plots visualize statistical relationships between variables, essential for predictive modeling and correlation analysis. This collection presents publication-quality regression plot examples from dose-response studies, calibration curves, and predictive models. Perfect for researchers performing linear regression, logistic regression, or non-linear modeling in experimental sciences. Learn to create informative regression plots with confidence bands, residual diagnostics, and model comparison using ggplot2, seaborn, and specialized statistical visualization packages.

18 plotsUpdated 7 days ago
Top 5 hits by combined score60of gene enrichment analysis employing enrichR for biological processes (2023) in either BioID or GFP-CoIP. Only GO terms with an adjustedpvalue <0.05 were included.
Enriched pathways and GO terms in sheep or goats identified using g:Profiler among the genes for reproduction traits under convergent selection. Circle size indicates the number of genes from the common gene hit list included in each enrichment item, and circle color and x -axis position indicate the P value. The vertical dashed lines indicate the significance threshold of FDR < 0.05.
Dot plot displaying the expression of significant ligandreceptor pairs in the NRG, CADM, NEGR and laminin pathways from all senders to hippocampal microglia ( PCDH9 high ). P values are computed from a onesided permutation test according to CellChat.
Schematic representation of mutant clones in an average 1 cm 2 of normal esophageal epithelium from a 48-51-year-old male donor from ref. 1 . To generate the figure, a number of samples from the donor are randomly selected and the mutant clones detected are represented as circles and randomly distributed in space.

Bubble Plot

Bubble Plots elegantly visualize three-dimensional data relationships through position and size encoding, ideal for multivariate scientific data analysis. This collection presents sophisticated bubble plot examples from genomics, epidemiology, and environmental science publications. Perfect for researchers visualizing gene expression with p-values, population health metrics, or ecological abundance data. Explore advanced techniques for creating informative bubble charts with proper scaling, color coding, and annotations using ggplot2, plotly, and D3.js for interactive scientific data visualization.

17 plotsUpdated 7 days ago
Examples of flight trajectories.
Areas of high (yellow) and low (purple) shipping traffic density from a 2019 monthly average (left) and areas of habitat suitability gain (red) and loss (blue) predicted from GAMs (right) shown in the national waters in the United States of America, marine region identification (ID), US part of the north Pacific Ocean.
Left: an example CBRS (treatment) area, with its spillover area (2 km buffer).
ASR(W)=age-standardised incidence rates.

Geo Map

Geo Maps (choropleth maps) powerfully visualize spatial data patterns in epidemiology, ecology, and public health research. This collection features high-quality geographic visualizations from disease surveillance, environmental monitoring, and population health studies. Essential for researchers analyzing geographic disparities, disease spread, or environmental gradients. Discover techniques for creating informative maps with proper projections, color scales, and statistical overlays using R packages like ggmap, leaflet, and specialized GIS tools for scientific spatial data visualization.

17 plotsUpdated 7 days ago
Comparison of high-risk sensitivity (for basal cell carcinoma, melanoma and SCC/SCCIS) versus fairness gap with regard to sex in dermatology across different baselines. We report results in-distribution (left) and OOD (right) for OOD 1, as well as for the less skewed (top) and more skewed (bottom) setting. We marked the baseline Pretrained on JFT with black. Label conditioning and Label and property conditioning correspond to the models that used synthetic images sampled from a diffusion model conditioned on only the label, and the label and sensitive attribute, respectively. We further compared to other strong contenders, that is, a BiT-ResNet model pretrained on ImageNet-21K (Pretrained on IN-21K), a model pretrained on JFT using RandAugment heuristic augmentations (RandAugment), a model trained with RandAugment on top of standard ImageNet augmentations (RandAugment + IN Augms), a model trained on a resampled version of the training dataset that is more balanced with regard to the sensitive attribute (Oversampling) and a model trained with focal loss (Focal loss). To ensure a fair comparison, all methods were trained and finetuned for the same number of steps and with the same batch size. For the fairness gap, smaller values are preferable. There are n = 1,349 samples in the in-distribution dataset and n = 6,639 samples in the OOD dataset. Data are presented as the mean s.d. across five technical replicates.
CV analysis (Wilcoxon test, θ = 17° ± 8°) agreed that CHX reduced release. Mean ± SEM.**p < 0.01,***p < 0.001.
Number of smSiP experimentally observed in smSiP–counting beads or PBS 1x–counting beads mixtures after the sorting of 500, 1,000 and 2,000 particles from smSiP at 0.05 mg ml −1 and PBS 1x solutions ( n = 5).
Pearson’s r between TWAS significances (color bar) of genes in pig BFT and their heritability enrichments (mean ± s.e.) in human weight. The orthologous genes were divided into ten evenly spaced bins by sorting the P values of TWAS in the brain of pig BFT. Shading: standard error of the fitting line.

Scatter Plot with Error Bars

Scatter Plots with Error Bars combine data relationships with measurement uncertainty, crucial for rigorous scientific data presentation. This collection showcases publication-quality examples from experimental physics, analytical chemistry, and quantitative biology. Perfect for researchers presenting calibration curves, dose-response relationships, or correlation analyses with confidence intervals. Master techniques for properly displaying measurement error, propagating uncertainties, and creating transparent scientific figures using specialized plotting libraries and error propagation tools.

17 plotsUpdated 7 days ago
Tukey boxplot showing the fractions of depleted protein-coding/known non-essential genes in any of 1095 cell lines of the DepMap as well as depleted miRNAs/intergenic controls in any of 45 cell lines screened with lentiG-miR. Dashed horizontal lines illustrate the median fraction of depleted protein-coding/miRNA genes across the corresponding cell lines.
Dot plots of differential coaccessibility Spearman correlation coefficients (Δ S ATAC ( i , j )) before and after cohesin depletion for chromosomes 1–19 and X. Every circle indicates the value of the differential coaccessibility Spearman correlation coefficient per ACD pair. The red line indicates the median value, and the dotted line indicates the zero-change line. The statistics were derived from 15,308 intrachromosomal ACD pairs with quantifiable values over 20 different chromosomes.
PTNR ( f ) and proportion of productive tillers (PT%, g ) of the genotypes in a . n = 20 plants. PTNR, productive tiller number under LN condition/productive tiller number under HN condition.
RPE1 cells were treated as in (D). The measurements of the number of RPA2 foci/nucleus were carried out from 3 independent experiments. Dashed lines represent the mean value on the plots. Silencing efficiencies are shown in the right panel.

Raincloud Plot

Raincloud Plots represent the gold standard for transparent data visualization, combining raw data, distributions, and summary statistics. This collection features state-of-the-art raincloud plot examples from psychology, neuroscience, and biomedical research. Essential for researchers committed to open science and reproducible data presentation. Learn to create comprehensive raincloud plots showing individual points, density distributions, and box plot summaries using R raincloudplots, Python ptitprince, and custom implementations for maximum data transparency.

12 plotsUpdated 7 days ago
Raman spectra of bulk 2DWPN-1 and 2DWPN-1 flakes.
PSD of the time traces in a . The curves are shifted vertically, and areas under them are shaded for clarity.
Set of STML spectra taken across a PdPc-NiPc dimer with R 1.85 nm. QNiPc emission was strongest when the tip was parked on the PdPc with maximum distance to the NiPc, and it vanished as soon as tunneling into NiPc was possible (It= 100 pA, Vs= -2.5 V, and t= 120 s).
Simulation of crack-front pinning by two-dimensional random heterogeneity.

Ridge Plot

A Ridge Plot, also known as a joyplot, is a visually striking chart that allows you to compare the distributions of a continuous variable across several different categories. It consists of a series of density plots that are partially overlapped, creating an effect reminiscent of a mountain range. This arrangement makes it incredibly effective for visualizing how a distribution changes from one group to another, such as illustrating changes in temperature over different months or exam scores across various schools. The ridge plot offers a compact and compelling alternative to faceting, providing a clear, high-data-density view that is both informative and aesthetically pleasing.

12 plotsUpdated 29 days ago
Optical PCE histogram for this DCTH solar cell before (orange) and after (red) operation. Arrows are guides to the eye from fresh to operated.
Cross-sectional area of the regenerating myofibers characterized by centralized nuclei, described in g . n = 3 per group. Mean ± s.e.m.
Mass photometry (Refeyn) assays examining the binding of PglX WT (red), PglX NTD only (blue) and PglX Mutant (yellow), in the absence or presence of 120 bp dsDNA substrates. DNA 1, two BREX motifs, one on each strand; DNA 2, two BREX motifs, both on same strand; DNA 3, on BREX motif; DNA 4, no BREX motifs. Insets show larger complexes formed with DNA 3 and DNA 4 for PglX WT.
Number of transmembrane helices per subunit.

Histogram

A Histogram is a classic and essential tool for visualizing the distribution of a single continuous variable. It groups data into a series of bins or intervals and displays the frequency of observations in each bin as a bar. This provides a clear, at-a-glance understanding of the data's underlying distribution, including its central tendency, spread, skewness, and modality (the number of peaks). Histograms are fundamental to exploratory data analysis, helping you to understand your data's characteristics before applying more complex statistical methods. They are perfect for analyzing exam scores, heights, weights, or any numerical dataset.

12 plotsUpdated 29 days ago
Venn diagram illustrating the consistency of SVs between NanoStrand-seq, bulk PB-CCS, and bulk ONT-UL.
Overlapping genes from top 50 hits from each screen, genes are ranked by average effect size.
Numbers of overlapping genes from top 50 hits of each screen. Genes are listed by average effect size (Table S1).
Venn diagram of IDR distribution in BP1 orthologs from fungi (407 total, black). Among the fungal BP1 orthologs, the number of proteins containing IDR1 (327, green) and IDR2 (373, blue) is shown.

Venn Diagram

Venn Diagrams remain popular for visualizing set relationships and overlaps in biological and medical research. This collection features elegant Venn diagram examples from gene expression studies, taxonomic comparisons, and literature reviews. Perfect for researchers illustrating shared features, unique elements, or logical relationships between 2-5 sets. Explore modern approaches to creating proportional, aesthetically pleasing Venn diagrams using R VennDiagram, Python matplotlib-venn, and online tools for publication-ready set visualization.

11 plotsUpdated 7 days ago
Polar plots representing the phase difference between estimated (Est.) and simulated GT for 30 randomly chosen cells from one simulated dataset using VeloCycle (left) and DeepCycle (right). Each dot represents a cell, and lines connect the estimated phase assignment (light gray) to simulated GT (dark gray).
Diagram showing intra- (light purple) and inter-subunit (green) cross-linking of the neddylated (N8) CRL2FEM1Ccomplex in the presence of UBE2R2 and Sil1 peptide. Cross-links between FEM1C and UBE2R2 have been colored red.
Circular plot visualization of the single-cell networks constructed based on observed (left) and uniform (right) bouton data. We assigned the colors in the outer circle by the soma location of each neuron in the network. The middle circle indicates the largest three communities obtained using the Leiden algorithm, and the inner circle indicates the broad brain regions TH, STR, hippocampal formation (HPF), cortical subplate (CTXsp), and isocortex. The lines crossing the center of the circle indicate potential connections between individual neurons. We colored them according to the soma location of the pre-synaptic neuron.
Chord diagrams displaying the significant signaling networks between the stroma, epithelium, and immune compartments in mutants (left) and wild types (right). Each sector represents a distinct compartment, and the size of the inner bars represents the signal strength received by their targets. Up- and down-regulated signaling L-R pairs were identified based on differential gene expression analysis between mutants and wild types, with a log-fold change (logFC) of 0.2 set as a threshold. Communication probabilities for the L-R interactions were calculated after adjusting for the size of cell populations, and then aggregated on the signaling pathway-level. UMAP: Uniform Manifold Approximation and Projection.

Chord Diagram

Chord Diagrams elegantly visualize complex relationships and flows between multiple entities in network biology and systems research. This collection features sophisticated chord diagram examples from genomics, ecology, and social network studies. Perfect for researchers illustrating gene co-expression networks, species interactions, or collaborative networks. Master circular visualization techniques for showing weighted connections, directional flows, and hierarchical relationships using R circlize, D3.js chord layouts, and specialized network visualization tools.

11 plotsUpdated 7 days ago
Representative ideogram plot of a NanoStrand-seq library for primary mouse cells distinguishing three possible template strand inheritance patterns (WW, CC, CW) and visible SCEs and inversion events. Directional sequencing reads were aligned to the mm10 reference genome and read counts were plotted as horizontal lines for each chromosome.
For PromScan promoter assignment, windows are defined in regions of 1,001 bp around the TSS +/- 10 kb with an offset of 300 bp. PromScan classifies overlap with the TSS. Shown is the OLIG2 promoter with BPE-600.
Zfp574 Cut&Run and PRO-seq screenshots at the Rpl10 locus.
ChIP-seq of H3K9me3 surrounding the ura4::10XtetO-ade6+ reporter in indicated genotypes and tetracycline treatment. The ura4::10XtetO-ade6+ reporter is highlighted in red. Each ChIP-seq track corresponds to a 40 kb region. Enrichment in all samples is shown as normalized reads per kilobase million (RPKM).

Genome Coverage Profile

Genome Coverage Profiles visualize sequencing depth and read distribution across genomic regions, essential for next-generation sequencing (NGS) data analysis. This collection presents exemplary coverage plots from ChIP-seq, RNA-seq, ATAC-seq, and whole-genome sequencing studies published in high-impact journals. Ideal for bioinformaticians and genomics researchers analyzing peak calling, transcriptome profiling, and chromatin accessibility. Discover effective visualization techniques for IGV browser tracks, bedGraph files, and bigWig data using tools like deepTools, UCSC Genome Browser, and custom R/Python scripts for publication-quality genomics figures.

10 plotsUpdated 7 days ago
Genome-wide PBS values for reproduction traits between prolific sheep (WDS, HUS, SXW, FIN, GOT) and non-prolific sheep (BSB, SSS) populations.
The y axis shows the gene-based associations from the ACAT omnibus test including Firths logistic regression, SKAT and ACAT-V (two-tailed -log 10 ( P value)) plotted against genomic coordinates on the x axis (GRCh38). The dashed line indicates the exome-wide significance threshold ( P = 2.7 x 10 -6 ).
Introgression d f statistic estimated for different Timor hybrid derivatives. Colored lines above the axis mark regions of significant introgression in the line under inspection, and are colored by chromosome. The shared introgressed region on chromosome 4 is colored in purple and boxed. TIPs are represented as lines below the x axis and exhibit overlap with introgressed regions.
Example of lesion segregation pattern due to UV induced mutations (top) across all chromosomes of a single mitotic sister, and lack of phasing from ROS induced mutagenesis (bottom) in the same sister. Reference cytosine mutations are shown as yellow dots, whereas reference guanine residues are in blue. The y axis represents log2(distance to nearest neighbor), with G mutation distances converted to negative values to distinguish them from C residues. Chromosomal boundaries are denoted by black vertical dashed lines and chromosomes noted between the tracks. Horizontal dashed line represents a distance of 0.

Manhattan Plot

Manhattan Plots are essential for genome-wide association study (GWAS) visualization, displaying genetic variant associations across chromosomes. This collection features exemplary Manhattan plot examples from human genetics, plant genomics, and precision medicine studies. Indispensable for researchers identifying disease-associated SNPs, QTLs, or selection signatures. Learn to create publication-quality Manhattan plots with proper significance thresholds, gene annotations, and zoom regions using R packages like qqman, CMplot, and specialized GWAS visualization tools.

10 plotsUpdated 7 days ago
Kaplan-Meier survival graphs of mice with the indicated genotypes.
Incidence of cardiovascular (CV) death (primary outcome)
KaplanMeier curves for groups stratified by model predictions from the best performing among implementation approaches are shown for LUNG1. To ensure a fair comparison, we calculated the threshold to split the risk groups on the HarvardRT tuning set for each implementation. The 95% CI of the estimates is shown by error bands. The measure of centre for the error bands is the KaplanMeier estimate of the survival function. KaplanMeier curves for all approaches can be found in Extended Data Fig. 6.
Survival comparison of all evaluable rGBM patients with either negative/low (1, 2) or intermediate/high (3, 4) tumor CD3 IHC scores. Dashed lines depict medians in months (Mo). Median survival times with 95% CIs in parentheses are also indicated; NA means infinity. P values comparing survival distribution of each group using the two-sided peto-peto test are depicted.

Survival Curve

Survival Curves (Kaplan-Meier plots) are essential for time-to-event analysis in clinical trials and epidemiological studies. This collection showcases exemplary survival curve examples from oncology research, reliability engineering, and longitudinal studies. Critical for researchers analyzing patient outcomes, treatment efficacy, or failure time data. Master techniques for creating publication-quality survival curves with confidence intervals, risk tables, and log-rank test results using R survminer, Python lifelines, and specialized survival analysis packages.

10 plotsUpdated 7 days ago
ROC curves of the 17-gene signature predicting PKUF-01 response in the training (n = 106) and validation (n = 106) sets. Area under ROC curves (AUROCs) are indicated.
AUC for predicting whether the images come from the same patient when compared to another image (n = 100,994).
ROC curves for the strainRvsP classifiers retrained using leave-one-histology-cohort-out cross-validation. Model training and testing were repeated 100 times, with predictions averaged to account for model stochasticity.
Smoothed area under the curve (AUC)-receiver operating characteristics (ROC) plots for Ly6E(hi)neutrophils (95% CIs: 0.855–0.9705 (NSCLC - LC), 0.7913–0.9606 (Melanoma - MN)), absolute neutrophil count (Abs Neut) (95% CIs: 0.534–0.9328 (in NSCLC)) and tumor PDL1 IHC (95% CIs: 0.3554–0.9338 (in NSCLC)) in our cohort of patients (NR vs. R). Confidence intervals were determined using 1,000 stratified, bootstrap replicates.

ROC Curve

ROC (Receiver Operating Characteristic) Curves are standard for evaluating diagnostic tests and binary classifiers in biomedical research. This collection features exemplary ROC curve examples from clinical diagnostics, biomarker validation, and machine learning applications. Essential for researchers developing diagnostic tools, evaluating screening tests, or comparing classifier performance. Learn to create publication-quality ROC curves with AUC calculations, confidence intervals, and optimal cutoff points using R pROC, Python scikit-learn, and specialized diagnostic accuracy tools.

9 plotsUpdated 7 days ago
PCA on whole transcriptomes of expanding FeBOs derived from dorsal (green) or ventral (orange) forebrain as well as matured FeBOs (gray).
PCA on ECM proteomes of human fetal brain tissue, FeBOs, PSC-cortical spheroids, and unguided PSC-cerebral organoids. n = 3 replicates per condition.
Conventional PCA shows that greater size of the control candidate sets to be sampled deteriorates their quality, as can be seen by inclusion of samples of nontarget ancestry.
Principal component analysis (PCA) for eigenvalues of the ten key soil properties, including soil organic carbon (SOC), dissolved organic carbon (DOC), total nitrogen (TN), NO 3 – -N, available P (AP), pH, microbial biomass N (MBN), microbial biomass carbon (MBC), bulk density (BD), and soil water content (SWC). Each soil property was normalized as an individual CSHA (Cornell Soil Health Assessment) contributor to the overall soil health score.

PCA Plot

A PCA (Principal Component Analysis) Plot is a fundamental visualization for exploring high-dimensional data. PCA is a dimensionality reduction technique that transforms complex datasets into a smaller number of "principal components," which capture the most variance in the data. The resulting 2D or 3D plot allows you to visualize the main patterns, clusters, and outliers in your data that would be hidden in a high-dimensional space. It is widely used in fields like bioinformatics, finance, and machine learning to simplify data, identify underlying structures, and prepare data for further modeling. Use a PCA plot to gain a clear, interpretable overview of complex data relationships.

8 plotsUpdated 29 days ago
Sankey plot showed the amplification frequency of PRKDC, CDK4, and ROCK2 in the three pathological subtypes and three proteomic subtypes of melanomas.
Distribution of sponsor and collaborator types. DTx=digital therapeutics. NIH=National Institutes of Health.
Alluvial plot showing that all 9 recurrent transcriptional clusters are fed with cells belonging to distinct genetic subclones identified by CNV inference from gene expression profiles. See alsoFigure S1.
Sankey plots showing the changes in window-level heterogeneity during the neuronal differentiation process. To simplify, shared windows of four stages are grouped into four quartiles according to their heterogeneity values in each stage.

Sankey Diagram

Sankey Diagrams powerfully visualize flow quantities and transformations in energy systems, patient pathways, and material cycles. This collection showcases professional Sankey diagram examples from environmental science, healthcare analytics, and industrial ecology. Perfect for researchers illustrating energy flows, patient outcomes, or resource allocation in complex systems. Master techniques for creating informative Sankey diagrams with proper flow scaling, color coding, and interactive features using R networkD3, Python plotly, and specialized flow visualization tools.

8 plotsUpdated 7 days ago
Mapping of CMS on tumor samples stratified according to their predicted cell-of-origin. The P value shows the result of Fisher’s exact test.
Unipept metaproteomics analysis of upregulated microbial proteins (fold change > 2, pnom.< 0.2) in TH+-activated and ChAT+-activated mice (n = 7–9 mice per group). Source data for (E) and (F) can be found at https://github.com/mazmanianlab/Griffiths_Yoo_et_al/blob/main/proteomics/metaproteomics/Microbiome_associated_proteins.xlsx.
TRs in genic regions that are predicted to be benign, and their tissue expression.
Nightingale Rose Charts of multiple objectives analysis to assess the detailed functions 1for each crop rotation

Pie Chart

Pie Charts effectively communicate proportional data when used appropriately in scientific contexts. This collection showcases well-designed pie chart examples from taxonomic composition, budget allocation, and survey results in research publications. Ideal for researchers presenting simple compositional data, funding distributions, or categorical proportions. Discover best practices for creating clear, accessible pie charts with proper labeling, color choices, and 3D effects using standard plotting libraries and data visualization tools.

7 plotsUpdated 7 days ago
Donut plots of mating choices of D. melanogaster (b), D. mauritiana (c), D. simulans (d), and D. sechellia (e) males and females (bi – ei) for conspecific (grey segments) or hybrid (red segments) mating partners. White segments, no mating within 1 h. Two-tailed Fisher’s exact test, * p < 0.05; ** p < 0.01; *** p < 0.001; black asterisks, conspecific preferred; red asterisks, hybrid preferred; NS no discrimination. Hybrids are named first by the acronym of their mother and then by that of their father parent.
The predicted variant consequence of all unique ClinVar variants and submissions. NMD: nonsense-mediated decay, UTR: untranslated region
The reported inheritance of NDD disease-gene associations. AR: autosomal recessive, AD: autosomal dominant, XLR: X-linked recessive, XL: X-linked recessive or dominant, XLD: X-linked dominant
Distribution of 34 tumor types in N = 191 children included in the ISAC study.

Donut Chart

Donut Charts offer modern alternatives to pie charts for displaying proportional data with additional design flexibility. This collection presents well-designed donut chart examples from research funding visualization, sample composition, and survey results. Ideal for researchers creating infographics, dashboard displays, or presenting simple proportional data with aesthetic appeal. Explore techniques for creating effective donut charts with central annotations, nested rings, and interactive features using D3.js, Chart.js, and modern data visualization libraries.

6 plotsUpdated 7 days ago
UpSet plots demonstrate the distribution of the delta masses within multiple body parts in humans. Vertical columns in the UpSet plots represent the number of unique delta masses (intersection size), with their distribution in different body parts (horizontal columns on the left, called set size) shown as black dot(s). The intersections highlighted in red correspond to delta masses corresponding to modifications for which we have annotations, including proteinogenic amino acids. For example, the phenylalanine delta mass is one of 11 delta masses found in seven sample types, including stomach, gallbladder, blood, cecum, ileum, jejunum, and feces.
Tumor/normal comparison of the COLO829 cell line using two different sequencing technologies: ONT MinION and PacBio Revio. Highlighted are the tumor-specific SVs (in red), the normal/control-specific SVs (in green) and the technology-specific SVs (dashed lines). In the cancer-specific SV, we found variants overlapping with cancer-related genes, such as PTEN, PMS2, ARHGEF5, PAK2 and WWOX. Differences between ONT and Revio calls for the same cell line can be attributed to either technology differences or the evolution of the cell line through time.
UpSet plot showing exclusive combinations of HPO terms associated with gene-NDD associations, where the sum across all combinations corresponds to the number of cases in the gold section of the pie chart. HPO (Human Phenotype Ontology)
The upset plot shows the common set of UF risk loci across three different GWAS studies. The lead SNP from Gallagher et al. is indicated for the common risk loci. For the Fig. 2b, two-sided student t test was performed.

UpSet Plot

UpSet Plots revolutionize set intersection visualization, surpassing traditional Venn diagrams for complex multi-set comparisons in bioinformatics. This collection showcases advanced UpSet plot examples from genomics, proteomics, and systems biology publications. Essential for researchers analyzing gene set overlaps, pathway enrichment results, or multi-omics data integration. Master techniques for creating scalable, interpretable set visualizations using R UpSetR, Python pyupset, and interactive UpSet implementations for publication-quality combinatorial analysis figures.

4 plotsUpdated 7 days ago
PR curve analyses on the basis of classifying predefined sets of essential and non-essential sgRNAs.
Plots of the PR curves used to quantify the ability of AbNatiV to distinguish the VHH camelid test ( b ) or camelid diverse >5% ( c ) set from the other datasets (see legend, which also reports the AUC values). The baseline (dashed line) corresponds to the performance of a random classifier. The corresponding ROC curves are given in Supplementary Fig. 11 .
Plot of the PR curves of the classification of 196 human-derived therapeutics from 353 therapeutics of non-human origin (mouse, chimeric and humanized) carried out with AbNatiV (in red) and seven other computational methods (see legend, which also reports the AUC values). The baseline (dashed line) corresponds to the performance expected from a random classifier. Corresponding ROC curves can be found in Supplementary Fig. 10.

PR Curve

Precision-Recall (PR) Curves are essential for evaluating machine learning classifiers on imbalanced datasets in bioinformatics and medical AI. This collection features PR curve examples from diagnostic test evaluation, biomarker discovery, and predictive modeling studies. Critical for researchers developing clinical decision support systems or genomic classifiers. Learn to create informative PR curves showing AUC-PR, operating points, and confidence bands using scikit-learn, ROCR, and specialized ML evaluation tools for reproducible model assessment.

3 plotsUpdated 7 days ago
Sketch of two oppositely out-of-plane magnetized Co nanoislands probed with a magnetic Co-functionalized STM tip.
Peripheral nerve tissue response. Schematic of the intraneural biocompatibility experiment. A PI device with and without EGNITE is implanted in the tibial branch of the sciatic nerve of rats.
Schematic of the artificial retina integrated with the 3D LM microelectrodes in close proximity to the locally bumpy, retinal surface, due to the degeneration of photoreceptors. ONL, INL and GCL indicate the outer nuclear layer, inner nuclear layer and ganglion cell layer, respectively.

Illustration

An Illustration is a custom-designed visual used to explain a specific concept, process, or idea with clarity and impact. Unlike standardized charts, an illustration is tailored to the exact narrative you want to convey, using diagrams, icons, and graphics to make complex information intuitive and memorable. This is invaluable in scientific publications for explaining experimental setups, in educational materials for clarifying difficult topics, or in business for presenting strategic plans. A well-crafted illustration transcends data to tell a story, making it a powerful communication tool for engaging any audience and ensuring your core message is understood.

3 plotsUpdated 29 days ago
Representative quantile–quantile plot (whole-blood JTI model) displaying the observed and expected distribution of −log 10 (METSIM P values) for gene–metabolite entries with metabolic genes that pass the threshold P < 0.05 in the CLSA. Expected distribution was calculated based on all considered entries. The gray line is y = x ; the orange dashed line is the Bonferroni threshold based on gene–metabolite associations with all genes. P values (uncorrected) are from the TWAS METSIM analysis.
QQ plot for linear regression association statistics using summary genotypes counts from optimal control dataset (λ < 1.05) on common synonymous DNA variant.

QQ Plot

A QQ Plot (Quantile-Quantile Plot) is an essential statistical visualization tool for assessing data normality and comparing probability distributions in scientific research. This collection showcases high-quality QQ plot examples from peer-reviewed publications, perfect for researchers conducting statistical analysis, hypothesis testing, and data quality assessment. Whether you're performing regression diagnostics, analyzing residuals, or validating statistical assumptions, these curated QQ plots demonstrate best practices for creating publication-ready figures. Explore examples using R ggplot2, Python matplotlib, and other scientific visualization tools to enhance your statistical data analysis workflow.

2 plotsUpdated 7 days ago
Single nucleotide polymorphisms and deletions found in the glpT gene of SL1344 after murine infection described in Gul et al. 70 PLoS Biology 2023 (upper half) and enriched premature stop codons found in sequences of different S . Tm isolates identified in Cherry, GBE, 2020 (lower half). Created in BioRender. Santamaria de Souza (2025) https://BioRender.com/f23o207
Summary of findings. Brief ketamine treatment causes, after washout, long-term reductions in passivity and hypo-activation of astrocytes compared with control.

Conclusion Diagram

Conclusion Diagrams synthesize research findings into powerful visual summaries, perfect for scientific papers, conference presentations, and grant applications. This collection features exemplary conclusion figures that effectively communicate key takeaways, research implications, and future directions. Essential for researchers crafting graphical abstracts, summary figures, and visual conclusions that enhance manuscript impact. Discover best practices for integrating multiple data types, highlighting significant findings, and creating memorable visual narratives using professional design tools and scientific visualization software.

2 plotsUpdated 7 days ago
Corrected peak spike rates of corner cells (identified in convex-3) at the convex corners (270° versus 315°) in the convex-3 arena (two-tailed Wilcoxon signed-rank test: P = 0.85; n = 10 mice).
Cumulative count of the number of participants partaking in the study.

Line Plot with Scatter

Line Plots with Scatter Points combine trend visualization with raw data transparency, ideal for time-series analysis and model validation. This collection presents exemplary hybrid plots from longitudinal studies, growth curves, and kinetic analyses. Essential for researchers showing fitted models alongside experimental data, confidence intervals, or individual observations. Learn techniques for balancing line clarity with data point visibility using ggplot2, matplotlib, and specialized plotting libraries for creating informative scientific figures.

2 plotsUpdated 7 days ago