Computational biology is used to help identify drug and therapeutic targets quicker and more accurately than ever before.
Computational biologists work closely with ‘wet lab’ research scientists to help design experiments that will generate data about a specific area of interest. They then create a pipeline programme which will be used by the bioinformatician to order the data in a structured way before it is passed onto a bioinformatic analyst for interpretation. The analyst uses the data to spot patterns, trends and anomalies which identify biomarkers or genetic markers that affect disease.
Once markers have been identified, computational biologists use their extensive computer skills to generate and test hypotheses, for example for new therapeutic concepts, based on the findings.
Successful candidates in these very technical roles will ideally be educated to PhD level in a relevant discipline, such as computational biology, statistics or physics, and have experience of using computational approaches on real world problems. They also need a good understanding of data science languages such as R and Python.
Computational biologists work in academia as well as commercial settings, where they are particularly important in helping pharmaceutical companies find discovery targets and assist in drug discovery.
The average salary for a Computational Biologist role would be $100,200.
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