Dive into the world of sequence alignment in this comprehensive 1-hour 23-minute lecture. Explore the foundations of comparative genomics and evolution, and learn how to apply dynamic programming principles to solve complex alignment problems. Understand the power of computation re-use and discover the efficiency of alignment matrices, paths, and traceback methods. Delve into local alignment techniques and linear-time, linear-space algorithms. Finally, master advanced concepts such as hashing, BLAST, inexact matching, and PSI-BLAST. Gain valuable insights into aligning sequential datasets and models, essential for computational biology and machine learning applications.
Sequence Alignment and Dynamic Programming in Computational Biology - Lecture 4
Overview
Syllabus
Intro: Aligning Sequential Datasets/Models
Comparative Genomics & Evolution
Computation Re-use, Dynamic Programming
Dynamic Programming Principles and Fibonacci
Alignment Matrix, Paths, Traceback, 2^N-vs-N^2
Local Alignment, Linear-Time, Linear Space
Hashing, BLAST, Inexact Matching, PSI-BLAST
Taught by
Manolis Kellis
