Profiler

Profiler unifies data import, quality control, preprocessing, statistical testing, machine and deep learning, biomarker discovery, pathway and drug-target enrichment, and survival modeling within a single reproducible environment for multi-omics analysis.

Key Features:

• Multi-omics Data Support: Profiler supports proteomics, metabolomics, lipidomics, transcriptomics, genomics, and electroencephalogram data from raw or tabular inputs.
• Automated Preprocessing: The platform provides automated preprocessing and quality control for diverse omics datasets.
• Statistical and AI-Driven Analysis: Profiler integrates statistical methods, machine learning, deep learning, and artificial intelligence into a unified workflow.
• Biomarker Discovery: The platform enables biomarker discovery through advanced analytical methods.
• Survival Analysis: Profiler includes survival modeling capabilities for clinical and biological data interpretation.
• Biological Interpretation: The platform performs pathway enrichment, drug-target enrichment, and biological interpretation using enrichment analysis.
• Reproducible Reporting: Profiler generates fully traceable analysis reports within minutes.

Scientific Applications:

• Glioblastoma Proteomics: Profiler reproduced known molecular subtypes from glioblastoma proteomic datasets.
• Pancancer Analysis: The platform was applied to pancancer datasets to reveal potential therapeutic targets.
• Multi-omics Integration: Profiler supports systems biology and precision medicine research through integrated multi-omics analysis.

Methodology:

Profiler is built in Python with Streamlit and deployed on high-performance computing infrastructure.