update

Author: GuangchuangYu

content/contribution-data-visualization.md

@@ -15,18 +15,19 @@ title: "Visualizing Complexity: A Universal Ecosystem for Multi-Scale Scientific
 
 ## Defining the Standards: A Universal Framework for Multi-Scale Scientific Visualization
 
-Modern scientific discovery relies on the ability to transform high-dimensional data into intuitive, accurate, and reproducible visual narratives. My work has established a **comprehensive visualization ecosystem** that spans from foundational plotting algebra to specialized interpretation frameworks for phylogeny and functional omics.
+Modern scientific discovery relies on the ability to transform high-dimensional data into intuitive, accurate, and reproducible visual narratives. Our work has established a **comprehensive visualization ecosystem** that spans from foundational plotting algebra to specialized interpretation frameworks for phylogeny and functional omics.
 
 ## 1. Methodological Foundations: Bridging Systems and Logics
 
 
 
-To address the fragmentation of the R plotting landscape, I developed a suite of tools that unify disparate plotting systems and introduce rigorous layout algebra.
+To address the fragmentation of the R plotting landscape, we developed a suite of tools that unify disparate plotting systems and introduce rigorous layout algebra.
 
-*   **`plotbb` & `ggplotify` (System Interoperability):** `plotbb` brings the Grammar of Graphics to Base R, while `ggplotify` allows researchers to convert virtually any plot object (Base, Lattice, pheatmap, etc.) into a `ggplot2` compatible object, enabling unified themeing and assembly.
-*   **`aplot` & `aplotExtra` (Layout Algebra):** These packages introduce an algebraic approach to plot alignment, allowing heterogeneous subplots to reconcile their coordinate systems automatically.
-*   **`ggbreak` (Dynamic Range Logic):** Provides a seamless, non-destructive method for axis breaks, essential for visualizing datasets with extreme outliers or multi-scale distributions.
-*   **`ggtangle` & `ggfun` (Network & UX):** `ggtangle` reimagines network visualization within the tidy framework, while `ggfun` provides foundational utilities that enhance the developer and user experience across the ecosystem.
+*   **[plotbb](https://github.com/YuLab-SMU/plotbb) & [ggplotify](https://cran.r-project.org/package=ggplotify) (System Interoperability):** **plotbb** brings the Grammar of Graphics to Base R, while **ggplotify** allows researchers to convert virtually any plot object (Base, Lattice, pheatmap, etc.) into a **ggplot2** compatible object, enabling unified themeing and assembly.
+*   **[aplot](https://cran.r-project.org/package=aplot) & [aplotExtra](https://github.com/YuLab-SMU/aplotExtra) (Layout Algebra):** These packages introduce an algebraic approach to plot alignment, allowing heterogeneous subplots to reconcile their coordinate systems automatically.
+*   **[ggbreak](https://cran.r-project.org/package=ggbreak) (Dynamic Range Logic):** Provides a seamless, non-destructive method for axis breaks, essential for visualizing datasets with extreme outliers or multi-scale distributions.
+*   **[ggtangle](https://github.com/YuLab-SMU/ggtangle) & [ggflow](https://github.com/YuLab-SMU/ggflow) (Relational & Process Flow):** **ggtangle** reimagines network visualization within the tidy framework, while **ggflow** provides a dedicated grammar for flowcharts and transition processes, bridging the gap between static relationships and dynamic workflows.
+*   **[ggfun](https://cran.r-project.org/package=ggfun) (UX & Utilities):** Provides foundational utilities that enhance the developer and user experience across the entire ecosystem.
 
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@@ -43,12 +44,13 @@ To address the fragmentation of the R plotting landscape, I developed a suite of
 
 
 
-Beyond general-purpose utilities, I have pioneered visualization standards in specific high-impact biological domains.
+Beyond general-purpose utilities, we have pioneered visualization standards in specific high-impact biological domains.
 
-*   **Evolutionary Narratives ([Phylogenetic Contribution](file:///e:/git/mybook/yulab-smu.github.io/content/contribution-tree-data.md)):** Led by **`ggtree`**, **`ggtreeExtra`**, **`ggtreeSpace`**, and **`ggtreeDendro`**, this suite has redefined how tree-structured data—ranging from deep evolutionary relationships to hierarchical clustering (dendrograms)—is integrated with multi-omics layers, becoming the de facto global standard.
-*   **Functional Discovery ([Knowledge Mining Contribution](file:///e:/git/mybook/yulab-smu.github.io/content/contribution-knowledge-mining.md)):** **`enrichplot`** transforms abstract enrichment results into statistically rigorous and biologically intuitive visual insights, enabling the automated interpretation of massive omics datasets.
-*   **Sequence & Genomic Landscapes:** **`seqcombo`** and **`ggmsa`** provide a modular grammar for multiple sequence alignment and the visualization of **genomic reassortment** events. These tools facilitate the visual exploration of segmental exchanges and complex evolutionary associations, ensuring that structural and genomic conservation is accessible at multiple scales.
-*   **Single-Cell & Fine-Scale Omics:** **`ggsc`** and **`ivolcano`** address the unique needs of high-resolution data, providing specialized geometries and interactive exploration for single-cell clusters and differential expression.
+*   **Evolutionary Narratives ([Phylogenetic Contribution](/contribution-tree-data)):** Led by [**ggtree**](https://bioconductor.org/packages/ggtree), [**ggtreeExtra**](https://bioconductor.org/packages/ggtreeExtra), [**ggtreeSpace**](https://github.com/YuLab-SMU/ggtreeSpace), and [**ggtreeDendro**](https://bioconductor.org/packages/ggtreeDendro), this suite has redefined how tree-structured data—ranging from deep evolutionary relationships to hierarchical clustering (dendrograms)—is integrated with multi-omics layers, becoming the de facto global standard.
+*   **Functional Discovery ([Knowledge Mining Contribution](/contribution-knowledge-mining)):** [**enrichplot**](https://bioconductor.org/packages/enrichplot) transforms abstract enrichment results into statistically rigorous and biologically intuitive visual insights, enabling the automated interpretation of massive omics datasets.
+*   **Sequence & Genomic Landscapes:** [**seqcombo**](https://github.com/YuLab-SMU/seqcombo) and [**ggmsa**](https://bioconductor.org/packages/ggmsa) provide a modular grammar for multiple sequence alignment and the visualization of **genomic reassortment** events. These tools facilitate the visual exploration of segmental exchanges and complex evolutionary associations, ensuring that structural and genomic conservation is accessible at multiple scales.
+*   **Single-Cell & Fine-Scale Omics:** [**ggsc**](https://github.com/YuLab-SMU/ggsc) and [**ivolcano**](https://github.com/YuLab-SMU/ivolcano) address the unique needs of high-resolution data, providing specialized geometries and interactive exploration for single-cell clusters and differential expression.
+*   **Glycobiology & Complex Carbohydrates:** [**gglycan**](https://github.com/YuLab-SMU/gglycan) introduces a grammar for visualizing complex glycan structures. By supporting standard symbolic nomenclature (e.g., SNFG), it enables researchers to integrate glycomic data with other biological layers, bridging a critical gap in multi-omics synthesis.
 
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@@ -65,11 +67,11 @@ Beyond general-purpose utilities, I have pioneered visualization standards in sp
 
 
 
-To bridge the gap between abstract data and human intuition, I developed tools for semantic enrichment and professional branding.
+To bridge the gap between abstract data and human intuition, we developed tools for semantic enrichment and professional branding.
 
-*   **`ggimage` & `scatterpie`:** Extending the visual vocabulary of `ggplot2` to include external imagery and composite geometries (like pie-charts within coordinates), allowing for "presentation-ready" visuals.
-*   **`emojifont`, `shadowtext`, & `meme`:** Enhancing semantic storytelling through advanced typography and cultural icons. These tools improve optical clarity through text halos and allow for creative, engaging data interaction, bridging the gap between formal analysis and impactful communication.
-*   **`hexSticker`:** Revolutionizing how R developers brand their work. `hexSticker` has established the "Hex Logo" as the universal symbol of professional R package development.
+*   **[ggimage](https://cran.r-project.org/package=ggimage) & [scatterpie](https://cran.r-project.org/package=scatterpie):** Extending the visual vocabulary of **ggplot2** to include external imagery and composite geometries (like pie-charts within coordinates), allowing for "presentation-ready" visuals.
+*   **[emojifont](https://cran.r-project.org/package=emojifont), [shadowtext](https://cran.r-project.org/package=shadowtext), & [meme](https://cran.r-project.org/package=meme):** Enhancing semantic storytelling through advanced typography and cultural icons. These tools improve optical clarity through text halos and allow for creative, engaging data interaction, bridging the gap between formal analysis and impactful communication.
+*   **[hexSticker](https://cran.r-project.org/package=hexSticker):** Revolutionizing how R developers brand their work. **hexSticker** has established the "Hex Logo" as the universal symbol of professional R package development.
 
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@@ -84,7 +86,7 @@ To bridge the gap between abstract data and human intuition, I developed tools f
 
 ## Community Impact & Influence
 
-My visualization frameworks have achieved global adoption, with **multi-million downloads** and integration into hundreds of third-party packages. This work serves as the foundational infrastructure for modern bioinformatics visualization workflows, cited in top-tier journals world-wide.
+Our visualization frameworks have achieved global adoption, with **multi-million downloads** and integration into hundreds of third-party packages. This work serves as the foundational infrastructure for modern bioinformatics visualization workflows, cited in top-tier journals world-wide.
 
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@@ -93,9 +95,7 @@ My visualization frameworks have achieved global adoption, with **multi-million
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 + S Xu, M Chen, T Feng, L Zhan, L Zhou, __G Yu__<sup>\*</sup>. [Use ggbreak to effectively utilize plotting space to deal with large datasets and outliers](https://www.frontiersin.org/articles/10.3389/fgene.2021.774846). __*Frontiers in Genetics*__. 2021, 12:774846.
-
 + __G Yu__. Data Integration, Manipulation and Visualization of Phylogenetic Trees (1st edition). __*Chapman and Hall/CRC*__, 2022. doi: [10.1201/9781003279242](https://doi.org/10.1201/9781003279242)
-
 + S Xu, H Dai, X Bo, __G Yu__<sup>\*</sup>. [ggmsa: a visual exploration tool for multiple sequence alignment and associated data](https://doi.org/10.1093/bib/bbab222). __*Briefings in Bioinformatics*__. 2021, 22(6):bbab222.
 
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