skills.rest
franklee16
franklee16COMMUNITY
Explore all skills by this author →
GitHub

scientific-visualization

Create publication-ready multi-panel scientific plots with journal-aligned styling.

203|27|Updated Apr 19, 2026
Search Tags:#publication figures#scientific visualization#matplotlib style presets#colorblind accessibility#figure export dpi#multi-panel layouts
One-click install
npx skills add https://github.com/franklee16/academic-research-skills --skill scientific-visualization-franklee16
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scientific-visualization
Source: https://github.com/franklee16/academic-research-skills/tree/main/visualization/scientific-visualization
Command: npx skills add https://github.com/franklee16/academic-research-skills --skill scientific-visualization-franklee16

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) and scripts (resource) components.

What problem does it solve?

This skill reduces the time and iteration required to produce journal-quality figures by standardizing layout, typography, color accessibility, statistics presentation, and export settings. It helps researchers turn analysis outputs into figures that meet common publisher requirements without manual guesswork.

Core Features & Use Cases

  • Publication styling orchestration: Applies consistent, journal-oriented matplotlib/seaborn styling (e.g., Nature/Science/Cell presets) so axes, fonts, spines, and sizing look correct at submission time.
  • Accessibility-first color and design: Guides colorblind-safe palettes (Okabe-Ito, etc.), grayscale compatibility, and avoids problematic colormaps for scientific meaning.
  • Correct export for manuscripts: Uses figure export utilities to save in appropriate formats (PDF/EPS/SVG for line art; high-DPI rasters for images) and journal-specific DPI expectations.

Quick Start

Use the scientific-visualization skill to style and export a multi-panel manuscript figure as a PDF using the journal-appropriate format and accessible palette.

Frequently Asked Questions about scientific-visualization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create publication-ready scientific figures that meet journal requirements?▼

Publication-ready scientific figures require standardized layout, typography, color accessibility, and export settings. This skill applies journal-aligned matplotlib and seaborn styling presets for Nature, Science, and Cell to ensure axes, fonts, and sizing meet common publisher requirements without manual guesswork.

How do I apply matplotlib style presets for Nature, Science, or Cell journals?▼

Matplotlib style presets for Nature, Science, and Cell journals are applied through standardized seaborn and matplotlib configurations. This skill orchestrates consistent journal-oriented styling across axes, spines, fonts, and sizing so multi-panel manuscript figures maintain visual consistency at submission time.

What's the best way to ensure colorblind accessibility in scientific plots?▼

Colorblind accessibility in scientific plots is ensured by using colorblind-safe palettes like Okabe-Ito and verifying grayscale compatibility. This skill guides palette selection to avoid problematic colormaps, ensuring scientific meaning is preserved for readers with visual impairments across all exported figures.

Can I use seaborn and plotly workflows to build multi-panel layouts with significance markers?▼

Seaborn and plotly workflows support multi-panel layouts with significance markers and error bars. This skill provides formatting guidance for multi-panel figures, ensuring typography, labeling with units, and visual consistency across panels align with journal-specific publication standards.

What figure export DPI and formats are required for scientific manuscript submission?▼

Scientific manuscript figure export requires vector formats like PDF, EPS, or SVG for line art and high-DPI rasters for images. This skill applies references-driven export rules to match journal-specific DPI expectations, ensuring resolution meets publication standards for outlets like Nature and Cell.

Related Skills

Explore More Education & Research Skills→
Teng-bioTeng-bio
2

scientific-visualization

Create publication-ready scientific plots with matplotlib, seaborn, and plotly.

Community
Advanced
wsxwj123wsxwj123
7

scientific-visualization

Create multi-panel publication figures with colorblind-safe palettes and journal-compliant exports.

Community
Advanced
jkitchinjkitchin
34

python-plotting

Select and apply Matplotlib, Seaborn, or Plotly for Python visualizations.

Community
Intermediate
brainworkupbrainworkup
1

scientific-visualization

Generate publication-ready multi-panel figures with journal-specific styles and colorblind-safe palettes.

Community
Advanced