Making sense of big data: studying leukaemia in the USA and Sweden

One of the most pressing challenges facing scientists today is the quantity of data that it is possible to generate by various new techniques and experiments. The term ‘big data’ is used more and more to capture the complexities faced by researchers. Data sets have grown so large that they become almost impossible to analyse using traditional tools. It is no surprise that scientists are finding it hard, if not impossible, to cope with such a large volume of data and to derive any real biological meaning from their findings. In the field of molecular biology, for example, the trend towards ‘big data’ is rapidly accelerating rather than slowing down, as the benefits of working with ever-larger datasets is a vital part of the fight against human disease.

Data challenge
Dr Anna Andersson, a scientist studying childhood Leukaemia in the United States and Sweden, is just one expert faced with these challenges. She turned to Qlucore for help. Qlucore is based in Sweden and started as a collaborative research project at Lund University, supported by researchers in the Department of Mathematics and Department of Clinical Genetics, to address the vast amount of high-dimensional data generated from other microarray gene expression experiments. 

The complexity of Dr Andersson's research work means that interpretation of data is crucial. Indeed, being faced with the potential of the vast quantity of data generated by her research studies, the challenge has always been to be able to interpret data and to test different hypotheses very quickly.