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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2022/2023

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DRPS : Course Catalogue : School of Biological Sciences : Postgraduate

Postgraduate Course: Biological Databases (PGBI11129)

Course Outline
SchoolSchool of Biological Sciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryThis is a course on databases focused on how an understanding of the database design can be used to enhance our ability to access biological data. We consider the design concepts of representative databases, how the resource can be queried and how data retrieved. We use this knowledge to build a small database. This course will provide students with the ability to fully exploit the features of biological databases with the purpose of extracting biological knowledge from complex data.
Course description In this course we will discuss the design principles of databases and the systems used to build and access them using a range of biological databases as examples. We will query some of these databases and use knowledge of database design obtained from studying these examples to build our own database.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2022/23, Not available to visiting students (SS1) Quota:  30
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 10, Supervised Practical/Workshop/Studio Hours 20, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 68 )
Assessment (Further Info) Written Exam 50 %, Coursework 50 %, Practical Exam 0 %
Additional Information (Assessment) In-course assessment (50%) and exam (50%).

The in-course assessment will be to build a small custom database automatically using scripts written in R or Python. These scripts will query several different databases and build the results into one integrated custom database.
Feedback Students will be given individual feedback during the practical sessions. The quiz will provide mid-course feedback. The in-course assessment will be marked and returned before the exams. There will be a revision session to discuss course content before the exams and exam feedback will be given.
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S1 (December)2:00
Learning Outcomes
On completion of this course, the student will be able to:
  1. Understand the different design strategies used for biological databases and be able to identify the strengths and weaknesses of each strategy.
  2. Recognise generic features of a design in a given example database.
  3. Query databases and implement a small database using R or Python.
Reading List
No single textbook covers the whole course content but SQL will be an important technology and for this a useful book is Learning SQL: Generate, Manipulate, and Retrieve Data, Alan Beaulieu

General Reading:

Thessen, Anne E., and David J. Patterson. "Data issues in the life sciences."ZooKeys150 (2011): 15.

Sharma, Parva Kumar, and Inderjit Singh Yadav. "Biological databases and their application."Bioinformatics. Academic Press, 2022. 17-31.

Hassani-Pak, Keywan, and Christopher Rawlings. "Knowledge discovery in biological databases for revealing candidate genes linked to complex phenotypes. "Journal of integrative bioinformatics" 14.1 (2017).
Additional Information
Graduate Attributes and Skills Practice, Applied knowledge, skills and understanding. For example, Develop original and creative responses to problems and issues.

Generic cognitive skills. For example Knowledge that covers and integrates most, if not all, of the main areas of the subject/discipline/sector including their features, boundaries, terminology and conventions.

Communication, Numeracy and ICT skills. For example, use a wide range of ICT applications to support and enhance work at this level and adjust features to suit purpose.

Autonomy, Accountability and Working with Others. For example, exercise substantial initiative in professional and equivalent activities and take responsibility for own work.
KeywordsNot entered
Contacts
Course organiserDr Simon Tomlinson
Tel: (0131 6)51 7252
Email: simon.tomlinson@ed.ac.uk
Course secretaryMs Louise Robertson
Tel: (0131 6)50 5988
Email: Louise.K.M.Robertson@ed.ac.uk
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