Master of Science in Bioinformatics at University of Malta

This programme of study is also offered on a part-time basis. Please consult the Registrar’s website for more information pertaining to courses offered by the University.

Computer Systems have become ubiquitous in the analysis of data to further increase our knowledge in a particular domain. Molecular biology is no exception to this. More so, the amount of data generated in this area has increased exponentially in recent years (e.g. high throughput sequencing for DNA, RNA and DNA-protein interactions or protein structures), and we now require to design new algorithms to handle this data. This programme of study will focus on bioinformatics, the study of the computational aspects of molecular biology data underpinned by solid statistical knowledge. Whilst this course will mainly encourage methods development in Bioinformatics, applications of several bioinformatics tools to existing datasets will also be covered. Bioinformatics offers essential tools to wet laboratory scientists. 

This programme of studies will equip students with the computational, molecular biology and statistical knowledge required to build and run the computational tools which underpin novel discoveries in molecular biology.

Learning outcomes

Students participating in this programme will gain the following subject knowledge and understanding:
a) dogma of molecular biology (and exceptions to it),
b) genetics,
c) genome sequencing, alignment and variant calling,
d) gene function prediction and annotation,
e) structural bioinformatics (including protein structure prediction),
f) network analysis (gene regulatory networks, protein interaction networks, metabolic networks, signalling networks etc.),
g) systems biology,
h) computational drug discovery,
i) software development principles (including programming and database systems),
j) statistical techniques used to validate bioinformatics methods,
k) ethical implications in the field, and
l) use of bioinformatics tools and databases

Intellectually, skills gained by the students include: 
a) critical thinking (ability to read, assess, contrast and criticize scientific literature)
b) analyse data in a molecular biology setting
c) design a scientific study and execute it
d) test and evaluate scientific hypotheses (including tools built or used)
e) document scientific experiments
f) build models for molecular biology systems

Key/transferable skills gained by the student include:
a) programming in Python
b) application of statistical techniques (using R)
c) scientific writing (including publishing a paper and writing a dissertation)
d) orally present scientific material, to an intelligent lay audience
e) organise a bibliography (develop bibliographic skills)
f) gain wet-lab experience
g) undertake rigorous, original and valid scientific research 

Many of these skills are industry relevant and increase the student's employability.

Course intended for

Students with an undergraduate degree in a scientific, medical, computational or mathematical subject with a penchant for computing and interdisciplinary research. The student must be willing to cross-train in other areas they may not be familiar with (e.g. genetics, proteomics, statistics, computing). They should also possess a strong interest in applying their knowledge to discoveries in molecular biology.

Career opportunites and access to further studies

Graduates of this programme will gain access to a myriad of computational opportunities, both in industry and in academia, in the ever-growing life sciences field. These may include (but are not limited to); data analysis, software engineering and modelling opportunities in genomics, proteomics, drug discovery, systems biology, and, more generally, in healthcare and biomedical research. This course will equip the student with knowledge to pursue reading a doctoral degree in the areas of computational biology, bioinformatics, and cheminformatics.