CSCI4181/6802 Bioinformatics Algorithms / Winter 2022-2023
Updates
- New Lecture is up: 21 Artificial Neural Networks & Deep Learning - Alex Manuele [slides] [recording]
- New Assignment released: [Assignment 4 - Machine-Learning Prediction of AMR Phenotype]
- New Lecture is up: 20 Classifiers - Simple to Ensembles [slides] [recording]
- New Lecture is up: 19 Training ML Models [slides] [recording]
- New Lecture is up: 18 - Pangenome Read Alignment - Prof. Travis Gagie [slides] [recording]
- New Lecture is up: 16 Feature Selection and Visualisation [slides] [recording]
- New Lecture is up: 15 Bayesian Phylogenetic and Statitical Support [slides] [recording]
Course Description
Bioinformatics uses computational and statistical approaches to tackle questions of biological function and evolution. The goal of Algorithms in Bioinformatics is to introduce key applications of algorithms, data structures, and encodings to the analysis of large biological data sets. A recurring theme throughout the course will be the disconnect between algorithmic beauty and the horrifying realities of biological data. Every statistical model is violated and every classification comes with an asterisk, as we struggle with even the most basic concepts of 'gene' and 'species', and the challenges of understanding events that happened across ~3.5 billion years. In spite of these challenges, in this age of massive data sets we stand to learn a good deal if the computational tools we use are efficient, robust, properly validated, and correctly applied. The course covers major challenge areas in bioinformatics, each focused on an aspect of DNA or protein sequence analysis. The goal in each case is to define an overarching problem, and then explore different approaches that have been applied to solving that problem, with an emphasis on the match (or mismatch) between the algorithm and the underlying biological system.
2023 Course Details
- Tuesday & Thursday: 8:35-9:55, 1201 Mona Campbell Building
- Office: 4239 Mona Campbell Building, Studley Campus
- Email: finlay.maguire@dal.ca
- Office Hours: No fixed hours, email us for an appointment
- BrightSpace for assignment/paper review submission.
- Syallabus
- Majority of materials used in this class were originally created by Prof. Robert Beiko and modified (to greater and lesser degrees) by myself.
