bioinformatics

An Introductory Undergraduate course in Bioinformatics

View the Project on GitHub rsh249/bioinformatics

bioinformatics | An Introductory Undergraduate course in Bioinformatics
Contact Info:
Rob Harbert, rharbert [at] stonehill [dot] edu
Stonehill College

Course Description

This course introduces common concepts and tools in the field of Bioinformatics with a focus on developing a basic skill set for working with large biological data sets. The digital age has resulted in a period of rapid growth of data, and in biology this is revolutionizing how we look at the world. Understanding how the field uses computational tools to manage and study these massive datasets is a crucial skill set for the modern Biology student. This course will cover the major sources of data in biology and an overview of the myriad of computational tools available

Objectives:

After having completed Introduction to Bioinformatics you will be able to:

License:

License

Outline:

Introduction to Bioinformatics

Meeting 1: Welcome!

Meeting 2: Biology as a Data Science

Lab 1: Getting started with R

Meeting 3: Getting started with R + Big-Data in Biology Presentations/Discussion

Meeting 4: Data Visualization in R

Lab 2: Setting up Git in RStudio

Meeting 5: DNA Sequencing Technology

Meeting 6: Introduction to the Unix Shell

Meeting 7: Demystifying Algorithms

Meeting 8: Sequence alignment and BLAST

Lab 3: rBlast

Meeting 9: Metagenomics

Meeting 10: Metagenomics 2

Lab 4: Metagenomics Lab

Meeting 11: Phylogenetics

Meeting 12: Open Science, bioRxiv, and course projects

Meeting 13: Managing Bioinformatics software with R and Anaconda

Lab 5: Introduction to Genome Assembly

Meeting 14: More Assembly + Bash Scripting for reproducibility

Meeting 15: Bacterial Genome + Hybrid Assembly

Lab 6: Assembly Viewing + Gene Prediction

Meeting 16: R and Data Manipulation with ‘dplyr’

Meeting 17: R for geospatial analysis (or R as GIS)

Meeting 18: GBIF and geographic point-locality data

Lab 7A: HPC Access

Lab 7B: Spatial Sampling Bias

Meeting 19: ENMeval for SDM training

Meeting 20: SDM on HPC

Lab 8: Scaling up ENM on HPC

Meeting 21: Visualize ENM output