L07 Assemble Genome (Part-1) | Bioinformatics & Computing in Bangla скачать в хорошем качестве

L07 Assemble Genome (Part-1) | Bioinformatics & Computing in Bangla

In this lecture, we examine the computational foundations of genome sequencing and how large genomes are reconstructed from millions of small DNA fragments, known as reads. The video begins with a real-world motivation: why scientists sequence thousands of genomes and how genome sequencing has transformed medicine, agriculture, and biotechnology. We briefly review the history of genome sequencing, from Sanger’s method in 1977 to modern Next-Generation Sequencing (NGS) technologies that have reduced the cost of sequencing a human genome from billions to just a few thousand dollars. Next, we introduce the central challenge of genome assembly: modern machines cannot read an entire genome directly, so they break it into short overlapping fragments. This leads to the String Reconstruction Problem, illustrated using the classic “Exploding Newspaper” analogy and DNA examples. You will learn: • What k-mers are and how to compute k-mer composition • How genome reconstruction can be modeled as a graph problem • Why naive reconstruction fails in many cases • How genome assembly can be formulated as a Hamiltonian Path Problem • How can it be transformed into an Eulerian Path Problem using De Bruijn graphs • The key difference between Hamiltonian paths and Eulerian paths By the end of the lecture, you will understand why De Bruijn graphs are fundamental to modern genome assembly algorithms and why Eulerian paths are more practical than Hamiltonian paths for sequencing. 📘 Reference: Bioinformatics Algorithms: An Active Learning Approach — Phillip Compeau & Pavel Pevzner 🎯 Best for: Bioinformatics students, computational biology learners, genome researchers, and anyone interested in how computers reconstruct DNA sequences.