In Silico Genomic Proteomic & Metabolomic Analyses Methods

Program Overview

This short course equips students with the knowledge and skills to analyze genomes, proteomes, and metabolomes using in silico methods. It introduces Python programming for data interpretation and covers applications in medicine, including diagnosis, treatment, and disease prevention. The course is suitable for students with a background in biosciences or related fields and can prepare them for careers in bioinformatics, genomics, proteomics, and other related fields.

Program Outline

In Silico Genomic Proteomic & Metabolomic Analyses Methods: A Detailed Extraction

Degree Overview:

This short course aims to equip students with the knowledge and skills needed to manipulate and analyze genomes, proteomes, and metabolomes using in silico methods. It also introduces the Python programming language and its applications in research and practice.

Objectives:

• To understand the need for efficient computational tools in gene, protein, and metabolite investigations.
• To integrate Python programming to interpret, critically evaluate, and present data analysis results.
• To gain practical experience using digital gene and protein sequence databases and expression analysis tools.
• To explore the applications of in silico methods in medicine, including diagnosis, treatment, and disease prevention.

Outline:

The course will be delivered online over 12 weeks, starting on January 27th, 2025. It will cover the following modules:

• Introduction to in silico methods: This module will provide a general overview of the theoretical basis and applications of in silico methods.
• Genome analysis: This module will focus on various methods for analyzing genomic data, including sequence alignment, variant calling, and gene expression analysis.
• Metabolome analysis: This module will delve into methods for analyzing metabolomic data, including metabolite identification, quantification, and pathway analysis.
• Case studies: This module will present real-world examples of how in silico methods are being used in different fields of research and medicine.

Assessment:

The course will be assessed through a combination of:

• Class test (50%): This written test will assess students' understanding of the key concepts and principles covered in the lectures.
• Set exercises (50%): These exercises will require students to apply the skills and knowledge gained in the course to solve real-world data problems.

Teaching:

The course will be taught by experienced faculty members from the School of Biomedical Sciences. The teaching methods will include lectures, interactive sessions, and hands-on practical exercises.

Careers:

This course can prepare students for careers in various fields, including:

• Bioinformatics
• Genomics
• Proteomics
• Metabolomics
• Drug discovery
• Personalized medicine
• Clinical research

Other:

This course is suitable for students with a background in biosciences, biostatistics, or related fields.

Northern Ireland, Republic of Ireland and EU Settlements Status Fees:

£583.35

England, Scotland, Wales and the Islands Fees:

£583.35

Additional mandatory costs

It is important to remember that costs associated with accommodation, travel (including car parking charges) and normal living will need to be covered in addition to tuition fees. Where a course has additional mandatory expenses (in addition to tuition fees) we make every effort to highlight them above. We aim to provide students with the learning materials needed to support their studies. Our libraries are a valuable resource with an extensive collection of books and journals, as well as first-class facilities and IT equipment. Computer suites and free Wi-Fi are also available on each of the campuses. Students choosing a period of paid work placement or study abroad as a part of their course should be aware that there may be additional travel and living costs, as well as tuition fees.