Securing the future of research computing in the biosciences

• Published in: PLoS computational biology 2019-05, Vol.15 (5), p.e1006958-e1006958
• Main Authors: Leng, Joanna, Shoura, Massa, McLeish, Tom C B, Real, Alan N, Hardey, Mariann, McCafferty, James, Ranson, Neil A, Harris, Sarah A
• Format: Article
• Language: English
• Subjects: Animals; Archives & records; Artificial intelligence; Astronomy; Bioinformatics; Biological research; Biology and Life Sciences; Biotechnology; Carpentry; Computation; Computational Biology - trends; Computer and Information Sciences; Computer applications; Computer hardware; Computer simulation; Computer Simulation - trends; Data collection; Data Curation - trends; Data processing; Datasets; Electron microscopy; Engineering and Technology; Forecasts and trends; Genomics; Humans; Infrastructure; International agreements; Internet; Investment; Medical imaging; Microscopy; Models, Biological; Molecular biology; Particle physics; Proteins; Research and Analysis Methods; Signal transduction; Software; Software upgrading; Storage requirements; Technology application; Tomography; Training
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1006958

Improvements in technology often drive scientific discovery. Therefore, research requires sustained investment in the latest equipment and training for the researchers who are going to use it. Prioritising and administering infrastructure investment is challenging because future needs are difficult to predict. In the past, highly computationally demanding research was associated primarily with particle physics and astronomy experiments. However, as biology becomes more quantitative and bioscientists generate more and more data, their computational requirements may ultimately exceed those of physical scientists. Computation has always been central to bioinformatics, but now imaging experiments have rapidly growing data processing and storage requirements. There is also an urgent need for new modelling and simulation tools to provide insight and understanding of these biophysical experiments. Bioscience communities must work together to provide the software and skills training needed in their areas. Research-active institutions need to recognise that computation is now vital in many more areas of discovery and create an environment where it can be embraced. The public must also become aware of both the power and limitations of computing, particularly with respect to their health and personal data.