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Module Title
LM Introduction to Biology and Programming
School
School of Bioscience
Department
School of Biosciences
Module Code
03 37234
Module Lead
TBC
Level
Masters Level
Credits
10
Semester
Semester 1
Pre-requisites
Co-requisites
Restrictions
None
Exclusions
Description
This module will provide an introduction to biology and programming for students from any disciplinary background. The module will introduce foundational topics and concepts in biology, including the fundamentals of:
The nature of biology and computational biology.
The scientific process, including formulation of hypotheses and hypothesis testing.
The central dogma of molecular biology, including the nature of the genetic information, how it is stored, transmitted, transcribed and translated.
Mechanisms through which genetic information can change (DNA mutation, meiosis).
The regulation of gene expression.
The principles of evolution and natural selection.
The collection of data to measure biological processes, including genomic, epigenomic, transcriptomic, metabolomic and proteomic techniques.
The module will cover foundational topics in bioinformatics, including an introduction to:
Linux computing systems (Unix), shell commands (bash), and the Compute and Storage for the Life Sciences (CaStLeS) system.
General introduction to computer programming, code and algorithms including good practice in writing code and script writing.
The R and Python programming languages, including syntax, data types, control structures and functions, data input/output.
Basic data exploration and visualisation in R.
Learning Outcomes
By the end of the module students should be able to:
Describe the steps involved in measuring biological processes using a variety of omics techniques spanning genomics, epigenomics, transcriptomics, metabolomics and proteomics.
Identify appropriate omics techniques and explain/compare their relative merits and limitations for addressing specific questions in biology.
Apply knowledge of basic biological processes including molecular genetics to solve simple problems in transmission genetics and interpret biological datasets.
Apply knowledge of computing systems and communications to remotely connect to and use the University compute systems.
Combine simple Shell commands (bash) in a Linux system to build a pipeline to manipulate data files and extract basic information.
Apply the principles of good practice in computer programming to write code (in R or Python) to reproducibly analyse a biological dataset to answer defined questions (including data import, and manipulation).
Choose appropriate methods for data exploration and create simple graphics to visualise the patterns shown by a given biological dataset.
