📚 References

Several websites and scientific articles helped us better understand the project, both from an analytical and conceptual perspective.

Indeed, without a solid understanding of the biological aspects, it would not have been possible to effectively use computational tools for the development of this project.

This is precisely the essence of bioinformatics: a combination of biology and computer science aimed at analyzing biological data, generating hypotheses, and ultimately contributing to scientific theories.

Below is a list of the main resources that supported our understanding.

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🌳 Study of Phylogenetic Trees

What is a phylogenetic tree?

• Understanding phylogenetic trees
• Phylogenetic trees explanation (LibreTexts)

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🔬 Study of Robinson-Foulds Distance

What is the Robinson-Foulds distance?

• Understanding Robinson-Foulds distance

Mathematical mechanism

• Generalized Robinson-Foulds Metric (Research paper)

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🧠 Study of K-means Clustering

What is K-means?

• Understanding K-means clustering (IBM)

Mathematical mechanism

• Mathematics behind K-means

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🎯 Additional Insight

These resources were essential to:

• Understand the biological meaning of phylogenetic trees
• Learn how to measure similarity between trees using RF distance
• Understand how clustering algorithms like K-means can be applied to biological data

This interdisciplinary approach highlights the importance of combining biological knowledge with computational methods in modern scientific research.