You can download the lectures here. We will try to upload lectures prior to their corresponding classes. Majority of slides used in this class were originally created by Prof. Robert Beiko and modified (to greater and lesser degrees) by myself.

  • 01 Course Overview & Life at Resolution
    tl;dr: Overview of the course, motivational plagues, and biology background from DNA to Ecosystems
    [slides] [recording (previous offering)]
  • 02 Pathways & Central Dogma
    tl;dr: Foundational material on biochemical pathways and how central dogma determines how biological data is copied and interpreted by cells
    [slides] [recording]
  • 03 Molecular Evolution
    tl;dr: Foundational material on molecular evolution
    [slides] [recording]
  • 04 Encoding DNA and Proteins
    tl;dr: Strings and structures for encoding biological sequence data for computation
    [slides] [recording]
  • 05 Sequence Alignment - Definitions and Scoring
    tl;dr: How we define and score sequence alignments
    [slides] [recording]
  • 06 Optimal Alignment - Dynamic Programming
    tl;dr: How dynamic programming approaches can be used to generate optimal alignments
    [slides] [recording]
  • 07 Practical Approaches for Large Datasets: BLAST and Burrows-Wheeler Transform
    tl;dr: Overview of the key BLAST and BWT algorithms
    [slides] [recording]
  • 08 Multiple Sequence Alignment
    tl;dr: An overview of algorithms for aligning multiple sequences and introduction to sensitive algorithms for searching divergent sequences
    [slides] [recording]
  • 09 Hidden Markov Models
    tl;dr: Quick introduction to HMMs
    [slides] [recording (previous offering)]
  • 10 Genomic Assembly
    tl;dr: Assembly algorithms for recovering 1 genome from sequencing data
    [slides] [recording]
  • 10a Bacterial Pangenomics - Dr. Ryan Fink
    tl;dr: Motivating case study of how bacterial pangenomics are used in research presented by Dr. Ryan Fink (no-recording)
    [slides]
  • 11 de Bruijn Graphs and Metagenomic Assembly
    tl;dr: dBG methods and assembly algorithms for assembling mixed sequencing data from multiple genomes at once
    [slides] [recording]
  • 12 Searching Massive Read Datasets
    tl;dr: Overview of k-mer indexing approaches for querying massive raw sequencing datasets
    [slides] [recording]
  • 13 Introduction to Phylogenetics
    tl;dr: Basic concepts of phylogenetics, distance, and parsimony algorithms.
    [slides] [recording]
  • 14 Maximum Likelihood
    tl;dr: Using maximum likelihood methods to infer evolutionary trees
    [slides] [recording]
  • 15 Bayesian Phylogenetic and Statitical Support
    tl;dr: Using Bayesian methods to infer evolutionary trees and inferring the statistical support of different trees
    [slides] [recording]
  • 16 Feature Selection and Visualisation
    tl;dr: Introduction to methods for biological feature selection for machine learning.
    [slides] [recording]
  • 17 Networks & Lateral Gene Transfer - Prof. Robert Beiko
    tl;dr: Lecture by Prof. Robert Beiko on phylogenetic inference of LGT

  • 18 - Pangenome Read Alignment - Prof. Travis Gagie
    tl;dr: Guest Lecture by Prof. Travis Gagie on pangenome read alignment data structures
    [slides] [recording]
  • 19 Training ML Models
    tl;dr: Basics of classification and how we train and choose supervised learning models
    [slides] [recording]
  • 20 Classifiers - Simple to Ensembles
    tl;dr: Whirlwind tour of different supervised learning models
    [slides] [recording]
  • No Lecture
    tl;dr: No Lecture

  • 21 Artificial Neural Networks & Deep Learning - Alex Manuele
    tl;dr: Lecture by Alex Manuele on deep learning in biological datasets.
    [slides] [recording]