Bio-Informatics (or Computational Biology)
Bio-informatics is the specialist field which improves on methods utilised for the technical development of systems involved with identifying, referencing, organising, analysing and storing bio-data.
At SCR we believe that the effective use of Bio-Informatics skills and tools will prove increasingly critical to the success of the Life Science sector.
Many years ago the expression GI-GO (Garbage In, Garbage Out) was coined to explain how, if in-correct or in-sufficient data was fed into a programmable system, a research project or programme would not succeed. Today, however, projects may fail even with the utmost care being taken into the choice of data and how it is fed in. Unsuccessful projects cost many wasted hours of human endeavour, computational resources and valuable funding.
The issue, both today and going forward, is that specialist Life Science projects create such vast quantities of data in their research (00’s of Gigabytes, perhaps even terabytes of data, on a regular basis) it is difficult, almost impossible, to identify, reference, organise and analyse the data being produced either quickly enough or in enough detail to enable projects to succeed fully.
These huge data sets are known as “Big Data” and are so complex that “off the shelf” database management and data processing applications simply can’t cope. As such they require specialist Scientific and Technical resources working in HPC (High Performance Computing) environments.
Bio-Informatics uses many areas of computer science and mathematics such as algorithms and data-mining to help process and make sense of these “Big Data Sets”. The efficient and effective identification and application of Bio-Informatics resources will help critical projects to save time, save money and ultimately advance the frontiers of scientific knowledge for the benefit of all.
Commonly used tools in Bio-Informatics include C++, Java, C#, Perl, Python, R, Matlab as well as work-flow management systems such as Tavaxy, Galaxy, Taverna, Anduril, Chipster and Bio-Bike. An academic background with an MSc or PhD in Science or Computational Science is advantageous for this field.
We are always happy to discuss career options and resource solutions involving the above skills sets especially as, with our cross-sector experience, we know that the skills required in Bio-Informatics are also highly regarded and rewarded in Banking, Finance and Insurance.