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Updated: Mar 18, 2026

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Published on: October 27, 2017

Network-based pathway enrichment analysis with incomplete network information.

Jing Ma¹, Ali Shojaie², George Michailidis³

¹Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, PA 19104, USA.

Bioinformatics (Oxford, England)

|July 1, 2016

Summary

This summary is machine-generated.

This study introduces a novel framework for pathway enrichment analysis, integrating cell-specific Omics data with existing biological networks. The method enhances the accuracy of identifying biological pathway changes in disease states.

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A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

Area of Science:

Bioinformatics
Systems Biology
Computational Biology

Background:

Pathway enrichment analysis is crucial for understanding biological responses in diseases and treatments.
Existing methods often rely on incomplete or non-specific pathway network information.
Network-based approaches outperform simpler methods but require accurate, condition-specific data.

Purpose of the Study:

To develop a constrained network estimation framework for pathway enrichment analysis.
To integrate cell- and condition-specific high-dimensional Omics data with existing interaction databases.
To enable simultaneous testing of expression levels and interactions within biological pathways.

Main Methods:

Proposed a constrained network estimation framework.
Combined cell- and condition-specific Omics data with existing interaction databases.
Developed a framework for simultaneous testing of pathway member expression and interactions.

Main Results:

The framework provides accurate pathway topology information.
The method allows for simultaneous testing of expression levels and interactions.
Performance was evaluated using simulated and real data, demonstrating effectiveness.

Conclusions:

The proposed method offers an improved approach to pathway enrichment analysis.
Integrating Omics data with network information enhances biological insights.
The R-package netgsa is available for practical application.