Bioinformatics is an emerging and increasingly important scientific discipline dedicated to the pursuit of fundamental questions about the structure, function and evolution of biological entities through the design and application of computational approaches. Fundamental research in these areas is expected to increase our understanding of human health and disease, which translates into innovation in industry (i.e. drug discovery).

Bioinformatics applies principles of information sciences and technologies to make the vast, diverse, and complex life sciences data more understandable and useful. It involves, research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioural or health data, including those to acquire, store, organise, archive, analyse, or visualise such data.

Completion of the human genome signified a step change in life sciences from the consideration of biological components in isolation to approaches that attempt to profile global change and provide the base for true systems biology. Technical developments such as molecular genetics, transcriptomics, proteomics and metabolomics provide the analytical base to support this advance, but demand novel statistical and computational skills. In this post-genomic era, bioinformatics is rapidly developing and it is essential that current and future researchers learn the most up-to-date applications and approaches. Post-genomic applications demand a level of informatics skill beyond that previously employed in biosciences.

What is Bioinformatics?

Bioinformatics derives knowledge from computer analysis of biological data. These can consist of the information stored in the genetic code, but also experimental results from various sources, patient statistics, and scientific literature. Research in bioinformatics includes method development for storage, retrieval, and analysis of the data. Bioinformatics is a rapidly developing branch of biology and is highly interdisciplinary, using techniques and concepts from informatics, statistics, mathematics, chemistry, biochemistry, physics, and linguistics. It has many practical applications in different areas of biology and medicine including: sequence analysis, genome annotation, computational evolutionary biology, measuring biodiversity, analysis of gene expression, analysis of gene regulation, analysis of protein expression, analysis of mutations in cancer, prediction of protein structure, comparative genomics, modelling biological systems and high-throughput image analysis.

Bioinformaticians today must be able to appreciate significant research in other fields and therefore require an understanding of the basic principles of other disciplines. To meet this challenge, a Master of Science degree with specialization in Bioinformatics is introduced through the department of Computer Science in the College of Computer and Information Sciences at King Saud University.

Why Bioinformatics?

We are witnessing the birth of a new era in biology. The ability to decipher the genetic code of living organisms promises to improve the quality of human life and has dramatically changed the challenges that the biological and biomedical sciences can address.

On one hand, recent and novel technologies produce biological datasets of ever increasing size, regarding genomic sequences, RNA and protein abundances, their interactions with each other, their sub-cellular localization, and the identity and abundance of other biological molecules. This requires development of sophisticated computational methods (Bioinformatics). On the other hand, to understand life, biology can now rise to the challenge of understanding the integrated functions of thousands of genes (Systems Biology). Large physical and functional interaction networks gained through genetic, biochemical and pharmacological approaches reveal the connectivity of the network, identify functional modules and provide clues on the functioning of specific genes. Studies of network biology lead to the construction of predictive models that reveal mechanisms and allow for virtual experimentation.

Addressing these challenges and moving biology into the realm of a quantitative, predictive, and theory-driven science, will require an interdisciplinary research structure, where people from different disciplines can meet together to come up with brilliant solutions and ideas for a lot of biological problems. Disciplines, such as: Artificial Intelligence, Data Mining, Databases, Data Structures, Heuristic Algorithms, Pattern Recognition, Machine Learning and much more, have a lot of applications and tools that can be used to solve a lot of important biological problems. You don't need to be a biologist in order to work in this field. Biological background requirements are limited and depend on the problem that you will study.