# Recent Web Platforms for Multi-Omics Integration Unlocking Biological Complexity
## 2 Methods
### Platforms for Multi-Omics Visualization and Pathway Exploration
#### 2.2.5. PaintOmics 3: A Web-Based Pathway-Centric Tool for Multi-Omics Visualization  
PaintOmics 3 is a versatile web-based platform designed to facilitate pathway-level analysis and visualization of multi-omics data, integrating various omics layers such as transcriptomics, proteomics, metabolomics, and epigenomics. By allowing users to map omics data onto biological pathways, PaintOmics 3 helps researchers explore the complex interactions between molecular entities across different biological processes, making it particularly valuable for studies that require a pathway-centered analysis of omics data [22].  
One of the strengths of PaintOmics 3 lies in its interactive and customizable interface, which enables users to overlay different omics layers onto known pathways and dynamically visualize how molecular interactions unfold in response to experimental conditions. Users can explore enrichment, differential expression, and pathway consistency analyses, providing a comprehensive perspective on how alterations in one omics layer may affect others within the same pathway. This functionality makes PaintOmics 3 especially valuable for identifying potential regulatory elements and interactions that may not be detectable through single-omics approaches alone.  
Through PaintOmics 3, researchers without extensive bioinformatics expertise can access tools to visualize and interpret multi-omics data, thanks to the platform's user-friendly web interface and pathway-centric visualizations. While highly effective for exploring the relationships between multiple omics types within pathways, PaintOmics 3's focus on pathway visualization may limit its suitability for projects requiring in-depth statistical analysis or direct clinical decision-making. However, as a pathway-based visualization tool, it complements platforms like multiSLIDE and MVP by offering an accessible and intuitive approach to multi-omics exploration within known biological contexts.  
2.6. Argonaut: A Collaborative Multi-Omics Platform with Real-Time Statistical and Interactive Visualization Tools  
Argonaut is a collaborative, web-based platform that enables interactive exploration of multi-omic data through an intuitive and user-friendly interface. Designed for ease of use, Argonaut allows researchers to create customized data portals that can be securely shared and explored globally, making it a powerful tool for collaborative studies in multi-omics research [23]. By providing real-time statistical analyses and interactive visualizations such as volcano plots, PCA, and condition-correlation matrices, Argonaut supports efficient data exploration across multiple layers of omics without requiring advanced programming skills.  
A notable feature of Argonaut is its focus on accessibility and collaboration, which allows researchers from diverse backgrounds to interact with and interpret complex datasets. The platform's use of Docker containers ensures seamless setup and reproducibility, while its permission-based sharing system enhances collaborative workflows. Furthermore, Argonaut is designed to have a minimal learning curve, enabling users without bioinformatics expertise to quickly gain proficiency. The platform offers comprehensive documentation, user tutorials, and a supportive community to assist new users in navigating its features. These resources are particularly valuable for interdisciplinary teams, ensuring that researchers from various fields can utilize Argonaut effectively with minimal technical barriers.  
However, Argonaut's primary focus on data visualization and exploration may limit its application for users needing in-depth statistical analyses or pathway-centric tools. Nonetheless, Argonaut represents a significant advancement in making multi-omic data accessible to a broader scientific community, particularly for collaborative and interdisciplinary research environments.