Principles of Digital Biology

COMP60532 Principles of Digital Biology 15 Semester 2 Postgraduate Taught Level 6 Duncan Hull Unit coordinator 1 FHEQ level (Framework for Higher Education Qualifications) ' Masters/Integrated Masters P4 ' European Credit Transfer & Accumulation System Rating : 7.5 Biology is currently undergoing a revolution. The success of the human genome project and other high-throughput technologies is creating a flood of new data. Capturing, interpreting and analysing this data provides real and significant challenges for computer scientists. This course will use biology as an exciting application domain for a wide range of CS techniques that have been developed on the course. Biology is currently undergoing a revolution. The success of the human genome project and other high-throughput technologies is creating a flood of new data. Capturing, interpreting and analysing this data provides real and significant challenges for computer scientists. This course will use biology as an exciting application domain for a wide range of CS techniques that have been developed on the course.The course is organised in 4 sections:<ol> <li>basic introduction to modern biology and bioinformatics</li> <li>data capture</li> <li>data delivery</li> <li>data analysis</li></ol>Each section will commence with a short taught component delivered as research seminars. Assessments will be based on a short written report and presentations based on a case study that will be introduced at the start of the course. <ul id="docs-internal-guid-8028f260-7fff-68ac-f1cf-9f7913e8e73a"> <li>A basic understanding of the computational needs of modern biology.<wbr style="color: rgb(0, 0, 0); font-family: Times New Roman; font-size: 16px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px;" /></li> <li dir="ltr">Develop an understanding of the problems inherent in communicating with scientists from a different discipline.</li> <li dir="ltr">Develop the ability to reflect upon and synthesize a range of computational techniques to develop effective problem solving strategies in an unfamiliar problem domain.</li> <li dir="ltr">Develop the ability to communicate these strategies to non-specialists.</li></ul> Analytical skills Group/team working Innovation/creativity Leadership Project management Oral communication Problem solving Research Written communication <ul><li>Intro to Biology</li><li>Intro to Biology - the central dogma (2 hours)</li><li>Intro to genomics (2 hours)</li><li>Biology databases (2 hours)</li><li>Data capture</li><li>Capturing microarray data (1 hour)</li><li>Proteomics seminar (1 hour)</li><li>The gene ontology (1 hour)</li><li>Resource meta-data (1 hour)</li><li>Data delivery</li><li>HCI and bioinformatics (2 hours)</li><li>Dealing with heterogeneous, distributed data. (2 hours)</li><li>Bioinformatics and the grid (2 hours)</li><li>Data analysis</li><li>Integrated approaches to post-genome data (2 hours)</li></ul> Lectures1 day per week (5 weeks) 2 Written assignment (inc essay) 100% Students work on a group based project exploring the application of computer science to an industrially focussed digital biology problem. Every day each group reports back to the class on the work they have completed. Tutors provide detailed formative feedback after each of these presentations. The final assessment is an individual report based on the group work. Detailed individual feedback will be provided on short report plans before the final report is completed. Pre-requisitesA knowledge of modern biology is not a course prerequisite. MSc Adv Computer Science MSc Artificial Intelligence PGDT Taught Component Optional MSc Adv Computer Science Computer Security PGDT Taught Component Optional MSc Health Data Science PT MSc Health Data Science PGDT Taught Component Mandatory PG Dip Health Data Science PT PG Diploma Health Data Science PGDT Taught Component Mandatory PG Cert Health Data Science PT PGCert Health Data Sci (18) PGDT Taught Component Mandatory Health Data Science - CPD Health Data Science - CPD PGDT Taught Component Optional PG Dip Health Data Science FT PG Dip Health Data Science FT PGDT Taught Component Mandatory PG Cert Health Data Science FT PG Cert Health Data Science FT PGDT Taught Component Mandatory Y Lectures 35 0 115 Links related to COMP60532<ul> <li><a href="http://www.youtube.com/watch?v=Y-ojxkxrJ58" target="_blank">Short video showing the application of digital biology techniques to food security in East Africa</a>.</li></ul>