BME356 Functional Genomics End-Of-Course Assessment July 2025 | SUSS

INSTRUCTIONS TO STUDENTS:

This End-of-Course Assessment paper comprises FIVE (5) pages (including the cover page).
You are to include the following particulars in your submission: Course Code, Title of the ECA, SUSS PI No., Your Name, and Submission Date.
Late submission will be subjected to the marks deduction scheme. Please refer to the Student Handbook for details.

IMPORTANT NOTE

ECA Submission Deadline: 03 November 2025, 12 noon

BME356 ECA Submission Guidelines

Please follow the submission instructions stated below:

This ECA carries 70% of the course marks and is a compulsory component. It is to be done individually and not collaboratively with other students. You must submit it on time.

Submission

You are to submit the ECA assignment in exactly the same manner as your tutormarked assignments (TMA), i.e. using Canvas. Submission in any other manner like hardcopy or any other means will not be accepted.

Electronic transmission is not immediate. It is possible that the network traffic may be particularly heavy on the cut-off date and connections to the system cannot be guaranteed. Hence, you are advised to submit your assignment the day before the cutoff date in order to make sure that the submission is accepted and in good time.

Once you have submitted your ECA assignment, the status is displayed on the computer screen. You will only receive a successful assignment submission message if you had applied for the e-mail notification option.

ECA Marks Deduction Scheme

Please note the following:

• Submission Cut-off Time – Unless otherwise advised, the cut-off time for ECA submission will be at 12:00 noon on the day of the deadline. All submission timings will be based on the time recorded by Canvas.
• Start Time for Deduction – Students are given a grace period of 12 hours. Hence calculation of late submissions of ECAs will begin at 00:00 hrs the following day (this applies even if it is a holiday or weekend) after the deadline.
• How the Scheme Works – From 00:00 hrs the following day after the deadline, 10 marks will be deducted for each 24-hour block.
• Submissions that are subject to more than 50 marks deduction will be assigned zero mark. For examples on how the scheme works, please refer to Section 5.2 Para 1.7.3 of the Student Handbook.
• Any extra files, missing appendices or corrections received after the cut-off date will also not be considered in the grading of your ECA assignment.

Plagiarism And Collusion

Plagiarism and collusion are forms of cheating and are not acceptable in any form of a student’s work, including this ECA assignment. You can avoid plagiarism by giving appropriate references when you use some other people’s ideas, words or pictures (including diagrams). Refer to the complete information on Harvard referencing and citation: http://www.open.ac.uk/libraryservices/documents/Harvard_citation_hlp.pdf You can avoid collusion by ensuring that your submission is based on your own individual effort. The electronic submission of your ECA assignment will be screened through a plagiarism detecting software. For more information about plagiarism and cheating, you should refer to the Student Handbook. SUSS takes a tough stance against plagiarism and collusion. Serious cases will normally result in the student being referred to SUSS Student Disciplinary Group. For other cases, significant marking penalties or expulsion from the course will be imposed.

Responsible Use Of Generative AI Tools

While Generative AI tools such as ChatGPT can generate responses for you, it cannot understand the specific context of your assignment. This could result in irrelevant answers or errors which will impact negatively on your grades. If you must use these tools, it is your responsibility to check and validate the generated content and rephrase in your own words.

Remember that ideas and information taken from other sources, including those derived from the use of Generative AI tools such as ChatGPT, must be appropriately attributed. Note that Turnitin can detect both AI generated content and plagiarism, and you will be subject to the penalties outlined above.

For more information on the responsible use of generative AI tools and how to correctly cite them as a source, refer to SUSS Teaching and Learning Centre’s Academic Integrity course

Question 1a

Compare DNA microarray analysis and quantitative RT-PCR as techniques for measuring gene expression. In your answer, describe how each method works, the type of data they produce, and identify ONE (1) major limitation of each method.

(8 marks)

Question 1b

You are investigating how the expression of a specific gene changes in response to a drug treatment. Propose an experimental method to quantify this change in gene expression, and explain why this method is appropriate.

(7 marks)

Question 2a

Compare Sanger sequencing with a next-generation sequencing (NGS) method (such as Illumina or Nanopore). In your answer, explain the underlying principles of each method, and compare their throughput and typical read lengths.

(8 marks)

Question 2b

Discuss TWO (2) major limitations or challenges in analyzing high-throughput sequencing data. Suggest a possible solution or approach to address ONE (1) of the challenges.

(7 marks)

Question 3a

Compare the underlying principles of methods of SDS-PAGE and size exclusion chromatography (SEC) for  protein separation. Illustrate how each method separates proteins and explain the type of information each technique provides.

(7 marks)

Question 3b

Design a purification workflow to isolate a target protein from a complex mixture using an AKTA automated chromatography system. In your answer, outline the key steps you would take to purify a target protein, including at least ONE (1) chromatographic technique. Explain how you would confirm the purity of the final protein product.

(8 marks)         

Question 4a

Compare X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy as techniques for determining protein structure.  Describe the principle of each method and ONE (1) key advantage and ONE (1) key limitation of each.

(8 marks)

Question 4b

A novel protein has been discovered with no experimentally solved structure. Develop a strategy to predict the three-dimensional structure of this protein using computational tools, and evaluate how reliable the predicted model is.

(7 marks)

Question 5a

Compare the working principles of Surface Plasmon Resonance (SPR) and Bio-Layer Interferometry (BLI) for studying biomolecular interactions. Appraise ONE (1) advantage of each method.

(6 marks)

Question 5b

Design an experiment to determine the binding kinetics and affinity between a protein and its ligand using SPR or BLI. Your answer should outline how the experiment would be set up and how the binding data would be interpreted.

(8 marks)

Question 5c

Computational methods can complement experimental interaction studies. Explain why a computational approach (such as molecular docking) is suitable for predicting a protein–ligand interaction, and appraise ONE (1) limitation of this approach.

(6 marks)

Question 6a

Evaluate the contribution of the Human Genome Project (HGP) to the development of personalized medicine. Support your answer with ONE (1) specific example of how genomic information is used to tailor medical treatment to an individual.

(10 marks)

Question 6b

Propose how genomic sequencing and analysis can be utilized to track and manage an emerging viral outbreak. In your answer, discuss how viral genomic data could inform public health decisions and appraise ONE (1) challenge associated with this approach.

(10 marks)