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Area of Science:

Bioelectrical modeling
Genomics
Cancer research

Background:

Distinguishing cancerous from healthy Homo Sapiens colon genes is crucial for early cancer detection.
Traditional methods may lack the precision needed for subtle genetic differences.
Understanding gene behavior through biophysical models offers a novel diagnostic avenue.

Purpose of the Study:

To propose an electrical network model for analyzing Homo Sapiens colon gene behavior.
To differentiate between cancerous and healthy colon genes using bioelectrical properties.
To evaluate the model's performance using established metrics and frequency analysis.

Main Methods:

Individual amino acid models were constructed based on the hydropathy index of amino acid side chains.
Electrical network modeling was applied to represent gene behavior.
Phase and magnitude responses of the gene models were analyzed.
Performance was assessed using accuracy, sensitivity, and specificity, with Receiver Operating Characteristic (ROC) curve analysis.

Main Results:

The electrical network model demonstrated the ability to screen cancerous from healthy colon genes.
Model performance, measured by accuracy, improved with increasing frequency.
A maximum accuracy of 97% was achieved at a frequency of 10 MHz.
ROC curve analysis confirmed the model's effectiveness.

Conclusions:

Electrical network modeling provides a viable method for distinguishing cancerous and healthy Homo Sapiens colon genes.
The proposed bioelectrical approach shows high accuracy and potential for cancer diagnostics.
Frequency-dependent analysis enhances the performance of gene-based electrical models.