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Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

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G2PDeep-v2: A Web-Based Deep-Learning Framework for Phenotype Prediction and Biomarker Discovery for All Organisms

Shuai Zeng^1,2, Trinath Adusumilli¹, Sania Zafar Awan³

¹Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA.

|December 30, 2025

Summary

This summary is machine-generated.

G2PDeep-v2 is a new web platform that uses deep learning to predict phenotypes and discover genetic markers from multi-omics data. It simplifies complex data analysis for researchers studying traits in humans and plants.

Keywords:

automated hyperparameters tunning biomarker deep learning multi-omics phenotype prediction reproducibility web-platform

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Integrating and analyzing multi-omics data for phenotype prediction and marker discovery is complex.
Accessible tools are needed to combine deep learning, hyperparameter optimization, visualization, and downstream analysis.

Purpose of the Study:

To develop G2PDeep-v2, a unified web platform for phenotype prediction and marker discovery using multi-omics data.
To provide researchers with an accessible tool for analyzing complex traits across various organisms.

Main Methods:

Developed G2PDeep-v2, a web-based platform utilizing deep learning.
Implemented an interactive interface for creating and training deep learning models.
Integrated automated hyperparameter tuning on high-performance computing resources.
Included visualization tools for phenotype and marker predictions.
Enabled Gene Set Enrichment Analysis for significant markers.

Main Results:

G2PDeep-v2 facilitates phenotype prediction and marker discovery from multi-omics data.
The platform supports analysis across diverse organisms, including humans and plants.
Automated hyperparameter tuning and visualization enhance the analysis workflow.

Conclusions:

G2PDeep-v2 offers a powerful and accessible solution for multi-omics data analysis.
The platform aids in understanding the molecular mechanisms of complex traits and diseases.
It empowers researchers to advance studies in genomics and computational biology.