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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

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Mining, visualizing and comparing multidimensional biomolecular data using the Genomics Data Miner (GMine)

Carla Proietti¹, Martha Zakrzewski¹, Thomas S Watkins¹

¹QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.

Scientific Reports

|December 7, 2016

Summary

This summary is machine-generated.

Genomics Data Miner (GMine) software enables non-experts to analyze complex biological data. It supports in-depth analysis of genomics, transcriptomics, and proteomics datasets, revealing patterns in immune responses.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Multidimensional biomolecular datasets are complex and require specialized tools for analysis.
Non-experts often face challenges in mining, clustering, and comparing these datasets effectively.

Purpose of the Study:

To introduce Genomics Data Miner (GMine), a user-friendly online software for analyzing complex molecular datasets.
To demonstrate GMine's capability in facilitating accurate and in-depth analyses using various data-mining techniques.

Main Methods:

GMine offers a user-friendly interface with powerful visualization techniques for high-quality figure generation.
It incorporates a broad range of data-mining techniques, including univariate and multivariate statistical analysis, supervised learning, correlation networks, clustering, and multivariable regression.
The software focuses on multivariate techniques to attribute variance to multiple explanatory variables and confounders, with various normalization methods provided.

Main Results:

Reanalysis of proteome microarray data against Plasmodium falciparum supported immunity as a higher-order phenomenon, not antigen-specific.
Analysis of T cell gene expression identified differentially expressed immune-related genes, highlighting T cell plasticity and activation programs.

Conclusions:

GMine facilitates accurate and in-depth analysis of complex genomics, transcriptomics, and proteomics data for researchers.
The software empowers non-experts to perform sophisticated analyses and generate publication-ready figures.
GMine aids in understanding complex biological phenomena, such as immune responses and cellular activation programs.