The Computational Systems Biology Group at Children’s Medical Research Institute (CMRI) has designed a new computational tool suite to analyse big data to help uncover signalling pathways within cells. Signalling pathways control cell behaviour and communication between cells. Abnormal signalling pathways result in cancer and other disease states.

Details of the new tool suite were published in Cell Reports this week.

Modern research technologies are capable of generating huge quantities of data, and the biggest challenge now is to turn this wealth of information into knowledge that will help understand and treat diseases. This new computational tool, PhosR, can increase the value of laboratory research data by unearthing novel insights from existing and new datasets about the proteins in cells and tissues – revealing potential new drug targets for treating diseases.

PhosR can analyse ‘phosphoproteomic’ data which are key to understanding cellular signalling pathways. These data are generated via mass spectrometry research. PhosR was designed by Dr Pengyi Yang and three PhD students: Hani Kim, Taiyun Kim, and Di Xiao.

Mass spectrometry at CMRI can identify up to 5,000 proteins in a tissue, such as a cancer sample. This process generates an enormous amount of data, and data scientists, including CMRI’s Dr Pengyi Yang, are designing tools like PhosR to make better use of this big data.

“Mass spectrometry has revolutionised the way we study cell signalling, and the amount of data we can generate in the lab is outpacing the speed at which we can analyse the data,” Dr Yang explained. “With mass spectrometry, we can study thousands of proteins and their phosphorylation at once, so we can get the data of an entire system. This means medical research is increasingly dealing with big data.”

Dr Yang describes how improving data analysis is helping researchers extract more value from existing results. “Labs are pumping out data these days. We have a tremendous ability to generate data, but now researchers are asking: ‘is enough insight being extracted from the data?’ With analysis tools like PhosR, we are able to learn new things from existing and future mass spectrometry data. It’s like looking at a photograph and finding something important that was missed by everyone before. We’re helping others to look more closely at data and make new biological and medical discoveries.”

“At CMRI in particular, there is a lot of expertise and data generated in mass spectrometry-based phosphoproteomics. But there is a need for the whole research community to improve their computational abilities. My group is creating tools and contributing expertise that will extract maximum value from laboratory research.”

Dr Yang explained the collaborative nature of designing this new analysis tool that could be used by researchers around the world. “Hani Kim and Taiyun Kim [CV1] drove this project forward, but it’s really a team effort with researchers from David James’ Lab at Charles Perkins Centre, The University of Sydney. We’ve been working on analysing phosphoproteomic datasets for eight years. We’ve developed a lot of methodology, but this is the first time we’ve put all these tools together in a way that can be shared with the community. Tools that were only available in our own research are now able to help the worldwide research community perform analyses and discover new biological knowledge to help fight disease. It’s exciting.”