MSc Bioinformatics

University of Hertfordshire

This module equips students with essential computing skills for bioinformatics applications. It covers computer hardware, operating systems, algorithm design and programming, alongside various bioinformatics file formats. You will explore parallelisation and job scheduling as required in high-performance computing clusters. On this basis you will learn to work sustainably with large volumes of data in bioinformatics, and to develop and operate systems to process and analyse scientific data efficiently and reproducibly.

This module equips you with essential skills to understand and utilize core databases and bioinformatics tools. It provides comprehensive background knowledge and hands-on experience with computational techniques, enabling students to analyse and interpret large-scale datasets in genomics and proteomics. Through practical exercises and real-world applications, you will gain proficiency in managing and extracting meaningful insights from complex biological data, preparing them for research and professional roles in the field of bioinformatics.

This module aims to provide you with a comprehensive understanding of statistical methods and advanced machine learning techniques, focusing on their application to complex biological and chemical data. It emphasizes critical evaluation and synthesis of research findings, application of sophisticated algorithms, and integration of diverse data types. The module enhances problem-solving skills through practical tasks, fosters independent research capabilities, and promotes ethical and professional standards. By the end, you will be equipped to tackle real-world bioinformatics challenges using statistics and machine learning.

This module provides advanced bioinformatics skills, focusing on genome sequence generation and analysis using next-generation sequencing (NGS) technologies. You will gain practical experience with computational tools and specialist techniques applicable in complex contexts. Emphasis is placed on critical analysis and evaluation of incomplete or contradictory data. By the end of the module, you will be proficient in designing and implementing bioinformatics workflows for genome sequencing projects, capable of comprehensive data generation and analysis for research and clinical applications, while applying ethical and professional values.

In this module the principles, methods and skills that underpin ethical scientific research are explored to build a foundation for the final research project. Within this module you will be supported by a personal tutor with regular small-group tutor meetings as well as receive information in more formal lectures. Knowledge of research methods enables you to research, understand and later contribute to the academic literature. You will learn how to execute a group project to a fixed deadline and communicate the project to an audience.

The Research Project module involves developing research questions and hypotheses for a chosen topic, followed by a dedicated period of 7-8 weeks for full-time independent research under the guidance of a supervisor. The findings are compiled into a research report and discussed in an oral examination.

This module explores the application of bioinformatics in clinical settings. You will learn about various clinical conditions requiring bioinformatics support, including genetic disorders, cancer, and infectious diseases. The course covers key bioinformatics tools and techniques used in diagnostics, prognostics, and personalized medicine. Topics may include genomic data analysis, variant interpretation, pathway analysis, and integration of multi-omics data. Students will use their knowledge of tools and databases acquired through previous modules to develop skills in interpreting bioinformatics results in a clinical context.