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Decision Tree Regression Modeling for Beginners

Are you interested in predictive modeling but feeling overwhelmed by complex algorithms? Decision tree regression might be the perfect...

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Convolutional Neural Networks (CNNs) for Beginners and Their Role in Computational Biology

In the rapidly evolving field of computational biology, machine learning techniques have become indispensable tools for analyzing complex...

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Bioinformatics Applications for Hidden Markov Models

In the vast landscape of computational biology, Hidden Markov Models (HMMs) stand out as a powerful and versatile tool. These statistical...

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Our Research Projects

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Cardiovascular Risk Prediction Using VLDL-P and hsCRP

This project utilizes a hybrid CNN model to analyze VLDL-P and hsCRP rates, visualizing cardiovascular risk levels. A random forest regressor predicts hsCRP values from VLDL-P data, revealing a significant positive correlation between the two biomarkers.

Computational Inhibition of PARP-1 for Metabolic Health

A QSAR-based analysis using PaDEL descriptors and IC50 values identifies potential PARP-1 inhibitors. The study aims to mitigate obesity-related inflammation and improve insulin sensitivity, with efficacy confirmed through statistical testing.

COMING SOON: Mapping Protein Pathway Evolution in Osteosarcoma Using Hidden Markov Models

This project leverages a Hidden Markov Model (HMM) to trace the evolutionary changes in the protein pathways involved in osteosarcoma. By modeling the dynamic sequence variations, the HMM provides insights into the biological mechanisms driving tumor progression, aiding in the identification of potential therapeutic targets.

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