BIOC40080 Biochemical Research Strategies and Problem Solving

Academic Year 2023/2024

This module, which is core for Stage 4 of the BSc Honours degrees in Biochemistry and Molecular Biology, is an advanced course that examines key data analysis techniques and strategies that are central to research in biochemistry and molecular biology. The module requires prior knowledge of basic biochemical and molecular biology techniques and focuses on the analysis of both, standard and high content data sets. Data analysis will be linked to answering specific research questions, either from the students' own research projects or alternative examples provided.

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Curricular information is subject to change

Learning Outcomes:

On completion of this module, students should be able to:
1. Process experimental data and solve numerical problems in biochemistry.
2. Demonstrate skills using data analysis programmes, in particular GraphPad Prism and Excel.
3. Demonstrate application of relevant statistical methods and use statistical analysis to interpret experimental data.
4. Apply appropriate data analysis strategies to research problems and experimental approaches in biochemistry and molecular biology.

Indicative Module Content:

Student Effort Hours: 
Student Effort Type Hours
Lectures

8
Tutorial

6
Specified Learning Activities

20
Autonomous Student Learning

66
Total

100
Approaches to Teaching and Learning:
The module is divided into two parts, part 1 covers the analysis of standard data sets, while part 2 will focus on data sets from high-throughput analysis (proteomics/transcriptomics data). Each part is comprised of Interactive lectures, hands-on data analysis sessions, tutorials and an assignment
 
Requirements, Exclusions and Recommendations
Learning Recommendations:

knowledge of biochemical and molecular biology techniques
prior exposure to analysis and interpretation of experimental data


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Assignment 2 (large data sets) Varies over the Trimester n/a Graded No

25
Examination: 3hr computer-aided examination Week 12 No Standard conversion grade scale 40% No

50
Assignment: Assignment 1 (standard data sets) Varies over the Trimester n/a Graded No

25

Carry forward of passed components
Yes
 
Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

1. Prior to Assignment 1, students select data set and complete formative assignment activities. The formative student submissions will be discussed in dedicated class tutorial sessions. 2. For Assignment 2, students will work on their data analysis problems during a tutorial session, during which questions will be answered and feedback will be given by lecturers and teaching assistants (demonstrators) . 3. The individual assignments will be graded and feedback provided to individual students via VLE. 4. Upon request, students receive individual feedback on the final exam.

Name Role
Dr Seema Nathwani Lecturer / Co-Lecturer
Dr Jens Rauch Lecturer / Co-Lecturer
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 
Autumn
      
Lecture Offering 1 Week(s) - 6, 7, 8 Mon 14:00 - 14:50
Lecture Offering 1 Week(s) - 5 Mon 14:00 - 15:50
Lecture Offering 1 Week(s) - 8 Thurs 10:00 - 11:50
Tutorial Offering 1 Week(s) - 9 Thurs 10:00 - 11:50
Lecture Offering 1 Week(s) - 5 Thurs 11:00 - 11:50
Lecture Offering 1 Week(s) - 6 Thurs 13:00 - 14:50
Lecture Offering 1 Week(s) - 7 Thurs 13:00 - 14:50
Lecture Offering 1 Week(s) - 5, 6, 7, 8 Tues 10:00 - 10:50
Autumn