Difference Between Rooted and Unrooted Phylogenetic Tree Explained Simply


When you start learning bioinformatics, one of the first confusing terms you may come across is the phylogenetic tree. These trees are used to represent evolutionary relationships between species. But there are two main types – rooted and unrooted phylogenetic trees. Let’s break it down in very simple words.
A rooted phylogenetic tree is like a family tree. It begins with a root, which stands for the common ancestor. From this single root, branches spread out, showing how different organisms evolved over time. It gives a clear sense of direction – where things started and how species changed with evolution.
An unrooted phylogenetic tree, however, is different. It doesn’t begin with a root or ancestor. Instead, it only shows how closely related species are to each other. You can think of it as a web of connections, but without telling us who came first. This type is useful when we just want to see relationships without focusing on the evolutionary timeline.
So, the difference between rooted and unrooted phylogenetic tree is simple:
Rooted trees show ancestry and direction of evolution.
Unrooted trees only show connections between species, without pointing to a common starting point.
Both types of trees are important in bioinformatics. Rooted trees are used to study evolutionary history, while unrooted trees help in data analysis where the ancestor is unknown. Scientists use them in genetics, disease research, and even in developing medicines.
At LLRI, we make concepts like this easier for students, especially those from Tier 2 and Tier 3 cities. If you want to build a career in bioinformatics, you can explore our industry-focused courses.
👉 Read the full blog here: Difference Between Rooted and Unrooted Phylogenetic Tree
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Written by

Raosaheb Ambekar
Raosaheb Ambekar
Learning Labb Research Institute (LLRI) offers focused programs in Clinical Research, Medical Coding, and Bioinformatics, designed to provide a clear understanding of each field’s role in healthcare and life sciences. The clinical research course covers trial design and regulatory practices; medical coding teaches documentation standards like ICD-10 and CPT; and bioinformatics explores the analysis of biological data. With a blend of theory and industry exposure, LLRI’s curriculum helps learners understand practical applications, making it a valuable resource for students and professionals in life science domains.