About us

AboutThe creation of the Centre for Computational Biology (CCB) is a fantastic opportunity to combine many of the field’s components, from both the development and applications sides. Our plan revolves around the three major components of applications, training and development, disseminated through the many fields of expertise found within the diverse domains of the Colleges of Medical and Dental Sciences, Life and Environmental Sciences, and Engineering and Physical Sciences.

Mission Statement

  • To promote excellence in Computational Biology, Systems Biology, and Bioinformatics across the range of fundamental and applied sciences, in both the University and allied Health Care arenas
  • To federate expertise through world class, independent and collaborative research, as well as teaching to a broad audience ranging from undergraduates to health care professionals
  • To provide an environment, both physical and structural, to foster collaborative work and cross-pollination

Key strengths

A key strength of the CCB lies in its central role in the University rather than isolated within a single department, school or college.  This consensual position allows for both the concentration of shared expertise and resources as well as cross-pollination, playing into the strengths of University, while creating a new one.  As a physical place on campus where Bioinformaticians are gathered, CCB aims to facilitate interaction by welcoming and hosting, when possible, local and external collaborators.

Facilities

Connections with the Queen Elizabeth Hospital provide access to a diversity of data, ideal for population genetics.  Models and approaches used in these fields are expected to overlap, at least conceptually, with fields such as Environmental Genomics.  On the more analytical side, computing resources and skills being so important in bioinformatics, very close collaboration with the very strong School of Computer Science help provide an optimal environment in expertise, infrastructure and manpower.  A good example lies in the rapidly developing field of Metabonomics, increasingly important in both the medical and life sciences.  Robust analysis of data generated by Birmingham’s NMR facility remains a challenge, technically, mathematically and computationally, and does therefore benefit from a cross-disciplinary approach.  Finally, combination of these diverse networks will ensure a very broad scientific and educational outreach.

Partnerships

To allow for efficient partnership with these many fields, a large and diverse workforce is necessary.  Because of the difficulty in recruiting such specialised individuals, an important part of the effort goes into training to develop new bioinformaticians as well as to train further researchers in biology, computer science, etc.  In this context, the agreement with BGI is most useful.The organisation of training courses is therefore essential for the proper application and development of Bioinformatics.  Training reaches out to students with backgrounds as diverse as Biology, Computer Sciences and Statistics, and encompasses three parts, namely Core Knowledge, Global Bioinformatics and Specific Applications.  The first part is given in collaboration with the Schools of Mathematics (Statistics) and Computer Science to provide the basic understanding of genomics and analysis from design to computation.  The second, and largest, section covers both classic bioinformatics such as database access, mapping or microarray analysis, as well as more recent developments from Next Generation Sequencing, e.g. RNASeq, ChipSeq.  Finally, in Specific Applications, the focus is the many applications of Bioinformatics in collaboration with the relevant fields of Medicine or Environmental Genomics.  Lectures are given from both Bioinformaticians and relevant external speakers.

A strong and successful partnership has been formed with the Research Support Section of IT Services who have designed and built the core infrastructure to meet the challenging data analytics and storage needs of life sciences research. These IT specialists work with the CCB community to develop and deliver applications suites, tailored to our research needs. The team also delivers some core skills training, runs clinics and gets involved in key initiatives such as the Academic Programmers Special Interest Group (SIG). The expertise in technology and data science as well as the commitment of the Research Support Section provide essential underpinnings to the CCB.

Sponsors

The Centre for Computational Biology is supported by:ccb logos-510