Programme And Module Handbook
 
Course Details in 2025/26 Session


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Module Title LH Experimental design, analysis & interpretation of biochemical data
SchoolSchool of Bioscience
Department School of Biosciences
Module Code 03 24258
Module Lead Dr Scott White
Level Honours Level
Credits 20
Semester Semester 1
Pre-requisites LI Proteins and Enzymes - (03 23326)
Co-requisites
Restrictions None
Contact Hours Lecture-14 hours
Practical Classes and workshops-34 hours
Guided independent study-152 hours
Total: 200 hours
Exclusions
Description

This biochemistry module integrates knowledge and skills acquired in earlier years and aims to develop related practical, data handling and interpretation skills and to stimulate a critical appreciation of the appropriate use of analytical methods in the main areas of biochemistry.

Learning Outcomes By the end of the module students should be able to:
  • Evaluate the criteria for the application of different experimental approaches
  • Have gained experience at (a) research laboratory skills, (b) drawing inferences from experimental observations and (c) subsequent experimental design;
  • Have developed critical reasoning and data interpretation skills and related quantitative skills
Assessment 24258-02 : Scientific Paper : Coursework (50%)
24258-04 : Examination : Exam (School Arranged) - Computer-based (50%)
Assessment Methods & Exceptions Assessments: One summative continuous assessed element (45%):Writing a scientific paper, formatted for an international biochemical journal, reporting the findings of a mini research project and discussing results in the context of the scientific literature
Exam (55%) (Main or Supplementary Periods) A 3 hour exam paper consisting of two sections:Section A: (40% weighting) Data Interpretation – MCQ questions testing the understanding and interpretation of a scientific paper. The scientific paper used in the assessment is released to students prior to the exam. Students may bring an annotated paper copy of the paper to the exam.Section B: (60% weighting) Data Handling – Quantitative questions on the topics taught in the data-handling workshops and associated lectures and activities. All questions will be compulsory
Other
Reading List