This thesis combines laboratory experimentation with advanced data analysis to explore the complexity of snake venom. In the lab, the chemical composition of venom was studied using cutting-edge techniques that separate and identify its various molecular components. On the computational side, bioinformatics tools were applied to analyze and compare venom data from a wide range of snake species and families. This approach helped uncover patterns in venom composition and provided insight into how it varies across species, geographic regions, and evolutionary branches. Additionally, the research introduced new methods to group and compare venom components more efficiently, enabling faster and more scalable analysis for future studies. By integrating hands-on laboratory work with modern computational analysis, this thesis offers a clearer understanding of what snake venom consists of, how its components function, and why its makeup differs so widely.
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