ICM: a web server for integrated clustering of multi-dimensional biomedical data.

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Multi-omics data generation is increasing, necessitating integrated analysis for precision medicine.
• Current integrated clustering methods lack user-friendly interfaces for researchers without programming expertise.

Purpose of the Study:

• To present a web tool, Integrated Clustering of Multi-dimensional biomedical data (ICM), for intuitive multi-omics data integration and clustering.
• To facilitate the exploration of disease heterogeneity and identification of patient subgroups.

Main Methods:

• Development of a web-based platform (ICM) for fusing, clustering, and visualizing multi-dimensional biomedical data.
• Implementation of an interactive user interface for result modification and collaboration via Project ID.
• Inclusion of incremental clustering functionality for adding new sample data.

Main Results:

• ICM provides an accessible interface for researchers to perform integrated clustering of multi-omics data.
• Users can identify patient subgroups and explore disease heterogeneity through interactive visualization.
• The tool supports collaborative analysis and incremental updates with new data.

Conclusions:

• ICM addresses the need for an intuitive, web-based solution for integrated multi-omics data analysis.
• The tool empowers biomedical researchers to advance precision medicine by uncovering biological insights.
• ICM is freely available, requiring no login, promoting wider accessibility and adoption.