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Updated: May 10, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

Pathway Processor 2.0: a web resource for pathway-based analysis of high-throughput data.

Luca Beltrame¹, Luca Bianco, Paolo Fontana

¹Translational Genomics Unit, Department of Oncology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via La Masa 19, 20159 Milano, Italy.

Bioinformatics (Oxford, England)

|June 7, 2013

Summary

This summary is machine-generated.

Pathway Processor 2.0 analyzes high-throughput data using pathway-centric logic. This web application identifies differentially regulated pathways by converting gene expression into pathway expression.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

High-throughput data analysis requires sophisticated tools.
Pathway analysis is crucial for understanding biological processes.
Existing methods may not fully capture complex gene expression patterns.

Purpose of the Study:

To introduce Pathway Processor 2.0, a novel web application for analyzing high-throughput datasets.
To provide a pathway-centric approach for interpreting gene expression data.
To identify differentially regulated pathways in various biological datasets.

Main Methods:

Utilizes a pathway-centric logic for data analysis.
Incorporates established methods like Fisher's test and impact analysis.
Implements innovative methods to convert gene expression into pathway expression.

Main Results:

Enables the analysis of diverse high-throughput datasets (e.g., microarray, next-generation sequencing).
Facilitates the identification of differentially regulated pathways.
Offers a user-friendly web service for biological data interpretation.

Conclusions:

Pathway Processor 2.0 is a valuable tool for high-throughput data analysis.
The application enhances the identification of biological pathways.
It provides a flexible platform for researchers in genomics and bioinformatics.