7
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Securing the future of research computing in the biosciences

      other

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Author summary

          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.

          Related collections

          Most cited references35

          • Record: found
          • Abstract: not found
          • Article: not found

          Biochemistry. The resolution revolution.

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Biomolecular simulation: a computational microscope for molecular biology.

            Molecular dynamics simulations capture the behavior of biological macromolecules in full atomic detail, but their computational demands, combined with the challenge of appropriately modeling the relevant physics, have historically restricted their length and accuracy. Dramatic recent improvements in achievable simulation speed and the underlying physical models have enabled atomic-level simulations on timescales as long as milliseconds that capture key biochemical processes such as protein folding, drug binding, membrane transport, and the conformational changes critical to protein function. Such simulation may serve as a computational microscope, revealing biomolecular mechanisms at spatial and temporal scales that are difficult to observe experimentally. We describe the rapidly evolving state of the art for atomic-level biomolecular simulation, illustrate the types of biological discoveries that can now be made through simulation, and discuss challenges motivating continued innovation in this field.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Observing the cell in its native state: Imaging subcellular dynamics in multicellular organisms.

              True physiological imaging of subcellular dynamics requires studying cells within their parent organisms, where all the environmental cues that drive gene expression, and hence the phenotypes that we actually observe, are present. A complete understanding also requires volumetric imaging of the cell and its surroundings at high spatiotemporal resolution, without inducing undue stress on either. We combined lattice light-sheet microscopy with adaptive optics to achieve, across large multicellular volumes, noninvasive aberration-free imaging of subcellular processes, including endocytosis, organelle remodeling during mitosis, and the migration of axons, immune cells, and metastatic cancer cells in vivo. The technology reveals the phenotypic diversity within cells across different organisms and developmental stages and may offer insights into how cells harness their intrinsic variability to adapt to different physiological environments.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                16 May 2019
                May 2019
                : 15
                : 5
                Affiliations
                [1 ] School of Computing, University of Leeds, Leeds, United Kingdom
                [2 ] School of Pathology, Stanford University, Palo Alto, California, United States of America
                [3 ] Department of Physics, University of York, York, United Kingdom
                [4 ] Advanced Research Computing, University of Durham, Durham, United Kingdom
                [5 ] School of Business, University of Durham, Durham, United Kingdom
                [6 ] Information Services Division, UCL, London, United Kingdom
                [7 ] Astbury Centre for Structural and Molecular Biology, University of Leeds, Leeds, United Kingdom
                [8 ] School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom
                [9 ] School of Physics and Astronomy, University of Leeds, Leeds, United Kingdom
                National Institutes of Health, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Article
                PCOMPBIOL-D-18-01128
                10.1371/journal.pcbi.1006958
                6521984
                31095554
                b18e37c9-7e24-4f2f-89d0-a037d36d3465
                © 2019 Leng et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 1, Tables: 1, Pages: 15
                Product
                Funding
                JL would like to thank the UK Engineering and Physical Sciences Research Council (EPSRC, https://epsrc.ukri.org/) for her Research Software Engineering fellowship (EP/R025819/1). TCBM would also like to thank the EPSRC for his fellowship (EP/N031431/1). This work was supported in part through the EPSRC/BBSRC "Physics of Life" Network+ grant no. EP/P006639/1 ( https://bbsrc.ukri.org/). MS is grateful to the Arnold and Mabel Beckman foundation for her fellowship ( http://www.beckman-foundation.org/). MH acknowledges Creative Fuse North East, AHRC, AH/P005160/1 ( http://gtr.ukri.org/projects?ref=AH%2FP005160%2F1). Electron microscopy in the Astbury Biostructure Laboratory is supported by the University of Leeds and the Wellcome Trust ( https://wellcome.ac.uk/home) grants 108466/Z/15/Z and 208395/Z/17/Z. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Perspective
                Computer and Information Sciences
                Software Engineering
                Software Tools
                Engineering and Technology
                Software Engineering
                Software Tools
                Computer and Information Sciences
                Computer Software
                Computer and Information Sciences
                Computing Methods
                Cloud Computing
                Computer and Information Sciences
                Information Technology
                Data Processing
                Research and Analysis Methods
                Microscopy
                Electron Microscopy
                Electron Cryo-Microscopy
                Computer and Information Sciences
                Software Engineering
                Software Development
                Engineering and Technology
                Software Engineering
                Software Development
                Biology and Life Sciences
                Biochemistry
                Biochemical Simulations
                Biology and Life Sciences
                Computational Biology
                Biochemical Simulations
                Computer and Information Sciences
                Software Engineering
                Software Design
                Engineering and Technology
                Software Engineering
                Software Design

                Quantitative & Systems biology
                Quantitative & Systems biology

                Comments

                Comment on this article