BM70002W Assessment Brief 2023-24

Assessment Brief

This module aims to evaluate your understanding and proficiency in bioinformatics and genome analysis, and the application of machine learning and artificial intelligence (AI) in the field.The assessment comprises three elements, each designed to assess specific skills and knowledge.

Assessment Element A1 (10%): Practical - Two Logbooks (500 words) Deadline: Week 5 (Sunday 10 March 2024 23:59)

In this practical component, you maintain two logbooks documenting your hands-on experience in machine learning and genome data analysis.Each logbook should be no more than 250 words and should reflect your practical work,challenges encountered,problem-solving strategies, and any modifications or improvements made during the practical sessions.The logbooks should demonstrate your ability to apply theoretical concepts to real- world scenarios.

Assessment Element A2 (40%): Written Assignment - Critical Review of Research on Genome Data Analysis, Genetic Variations, and so on (1,000 words)

Deadline: Week 8 (Sunday 7 April 2024 23:59)

This written assignment requires you to critically review recent research articles related to genome data analysis and genetic variations using machine learning.Your review should include an analysis of methodologies, findings, and their implications in the field. Additionally, you should discuss the limitations of the studies and propose areas for further research.The assignment should be precisely 1,000 words, using Arial font, size 12, and double line spacing.

Assessment Element A3 (50%): Written Assignment - Genome Data Analysis Using Machine Learning and AI to Demonstrate Your Programming Skills (1,500 words)

Deadline: Week 12 (Sunday 5 May 2024 23:59)

In this assignment, you are tasked with conducting genome data analysis using machine learning and AI techniques.Demonstrate your programming skills by implementing relevant algorithms and machine learning models.

Provide a detailed explanation of your methodology, including data preprocessing, model selection, and evaluation metrics.Discuss the significance of your findings and their potential applications in genomics.The assignment should be precisely 1,500 words, using Arial font, size 12, and double line spacing.

This written assignment requires you to critically review recent research articles related to genome data analysis and genetic variations using machine learning.

Assessment Submission Guidelines:

· All assessments should be submitted electronically through the designated online platform (i.e. Blackboard Turnitin) by the specified deadline.

· Ensure that your submissions adhere to the specified formatting guidelines for font, size, and line spacing.

· Late submissions will be subject to penalties as outlined in the student handbook.

· Plagiarism and academic misconduct will be treated seriously and may result in disciplinary action.

This assessment is designed to assess your practical skills, critical thinking, and ability to apply theoretical knowledge in machine learning and genome data analysis. Good luck!

In this practical component, you maintain two logbooks documenting your hands-on experience in machine learning and genome data analysis

Assessment Criteria:

Assessment Element A1:

· Clear documentation of hands-on experience in machine learning and AI practical sessions.

· Evidence of proficient execution of tasks, including data preprocessing, model implementation, and troubleshooting.

· Reflection on challenges encountered during practical sessions and thoughtful consideration of problem-solving strategies.

· Identification and discussion of modifications or improvements made during the practical work.

· Clear and concise presentation of logbook entries.

· Effective communication of ideas, with well-structured entries.

Assessment Element A2:

· In-depth and critical review of recent research articles in genome data analysis and genetic variations using machine learning.

· Evaluation of methodologies, findings, and implications of the studies.

· Recognition and discussion of limitations in the reviewed studies.

· Constructive proposals for areas requiring further research in the field.

· Clear organisation and logical flow of ideas throughout the review.

· Effective transitions between different sections of the assignment.

· Strict adherence to specified formatting guidelines for font, size, and line spacing.

· Proper citation of sources using a recognised referencing style.

Assessment Element A3:

· Effective application of machine learning and AI techniques to conduct genome data analysis.

· Demonstration of advanced programming skills in algorithm implementation.