Overview
BMS353 - Bioinformatics for Biomedical Science – Module Co-ordinator: Dr Marta Milo
Research Software Support: the module is supported by principle of Open Data Science Initiative and Research Software Engineering in collaboration with Dr Mike Croucher
Semester 1B – Level 3 Biomedical Science 2019/2020
Description
This module aims to provide an understanding of the fundamental concepts and technologies underlying computational biology and bioinformatics. In particular it will provide biology students with concepts of Bioinformatics and Computational biology for the analysis of biological data.
Teaching Methods
Teaching in BMS353 will be by a multidisciplinary approach, where conventional lectures will be integrated with practical implementation of concepts using programming tools and cloud environment. Lectures will introduce students to statistical concepts underpinning advanced data analysis and methods that are suitable for high-throughput data analysis. Theoretical concepts and detailed examples will be introduced in the lectures and implemented during the practical sessions. This is to provide students with key steps to perform experimental design in data collection, data analysis and results validation.
The course will present state-of-the art research in computational biology with guest lecture and enable students to critically assess statistical methods and enhance innovative thinking in data analysis. Both lectures and practical sessions will be interactive where students questioning and interaction is welcome. A web-based discussion environment will be used as a teaching tool where “Questions and answers” can be led by students and used as a forum for posting comments and suggestions.
Study time for this module
BMS353 module is a 10 credit module, where you are expected about 18 contact hours, with each requiring 3 hours of additional study. The module and the practical coursework are designed for the students to complete them within this time range. However, every student has a different learning pace and you can dedicate as much extra time you prefer, should you find the work interesting and want to stretch it further. Dedicated help and support will be provided and being the coding based on an open source platform, the best support is offered by online forums and guided examples. The lecturer will direct and guide you in any additional work.
The teaching consists of two hours of lectures and two of lab classes each week.
Given the complexity of the time table this academic year, please make sure you check on MOLE for the correct location and time of the lectures and practicals. The teaching schedule and venues for each week are given here.
Rooms Location
Room code | Building | Room |
---|---|---|
BH- ALG04 | Bartolome House- Computer Room | ALG04 |
AT- CR2 | Arts Tower- Pool Computer Room | CR 1012 |
AT-LT03 | Arts Tower | LT03 |
Lectures
Week 7 Introduction to the Course and the Tools Monday, November 11 at 12:00 (2 hrs) in AT-LT03
Week 8 Concepts of Statistics and their Implementation for Data Analysis Monday, November 18 at 12:00 (2 hrs) in AT-LT03
Week 9 Bioinformatics for High Throughput Data Monday, November 25 at 12:00 (2 hrs) in AT-LT03
Week 10 Gene Expression Analysis, use of Bioconductor and Limma Monday, December 2 at 12:00 (2 hrs) in AT-LT03
Week 11 High Level gene expression Analysis. Functional Annotation and Pathway Analysis Monday, December 9 at 15:00 (2 hrs) in AT-LT03
Week 12 Project Allocation and Discussion Monday, December 16 at 15:00 (2 hrs) in FC- F02
Lab Classes
Week 7 Basics of Data Manipulation Using Scripts Monday, November 11 at 15:00 (2 hrs) in AT-CR2 and BH-ALG04 (on Tuesday, November 12th at 15:00)
Week 8 Basics of Data Manipulation Using Scripts Monday, November 18 at 15:00 (2 hrs) in AT-CR2 and BH-ALG04 (on Tuesday, November 19 at 15:00)
Week 9 First steps analysis of High Throughput Data Monday, November 25 at 15:00 (2 hrs) in AT-CR2 and BH- ALG04 (on Tuesday, November 26th at 15:00)
Week 10 Analysis of High Throughput Data with Bioconductor and Limma Monday, December 2 at 15:00 (2 hrs) in AT-CR2 and BH-ALG04 (Tuesday, December 3rd at 15:00)
Week 11 Implementation of high level Gene Expression Analysis and Functional/Pathways Analysis Monday, December 9 at 12:00 (2 hrs) in AT-CR2 and BH-ALG04 (on Tuesday, December 10th at 15:00)
Week 12 Experimental Design, Projects Pipelines and Tutorial workshop Monday, December 16 at 15:00 (2 hrs) in AT-CR2 and BH- ALG04 (on Tuesday, December 17th at 15:00)