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Julia for biologists

Nature Methods volume 20, pages 655–664 (2023)Cite this article

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An Author Correction to this article was published on 29 April 2023

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Abstract

Major computational challenges exist in relation to the collection, curation, processing and analysis of large genomic and imaging datasets, as well as the simulation of larger and more realistic models in systems biology. Here we discuss how a relative newcomer among programming languages—Julia—is poised to meet the current and emerging demands in the computational biosciences and beyond. Speed, flexibility, a thriving package ecosystem and readability are major factors that make high-performance computing and data analysis available to an unprecedented degree. We highlight how Julia’s design is already enabling new ways of analyzing biological data and systems, and we provide a list of resources that can facilitate the transition into Julian computing.

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Fig. 1: Julia is a tool enabling biologists to discover new science.
Fig. 2: Overview of Julia’s package ecosystem, presented by topic group.
Fig. 3: Julia’s speed feature.
Fig. 4: Interfaces in Julia.
Fig. 5: The abstraction feature in Julia.
Fig. 6: Julia’s metaprogramming feature.

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Acknowledgements

We thank all attendees of the Birds of a Feather session Julia for Biologists at JuliaCon2021; D. F. Gleich for allowing us to run an experiment on his servers; and R. Patro for discussions about Rust. E.R. acknowledges financial support through a University of Melbourne PhD scholarship. A.L.M. acknowledges support from the National Science Foundation (DMS 2045327). T.E.H. acknowledges NIH 1UF1NS108176. The information, data and work presented herein was funded in part by the Advanced Research Projects Agency—Energy under award numbers DE-AR0001222 and DE-AR0001211, as well as National Science Foundation award number IIP-1938400. The views and opinions of the authors expressed herein do not necessarily state or reflect those of the US Government or any agency thereof. M.P.H.S. acknowledges funding from the University of Melbourne Driving Research Momentum initiative and Volkswagen Foundation Life? program grant (grant number 93063), as well as support through an Australian Research Council Laureate Fellowship.

Author information

Authors and Affiliations

  1. School of Mathematics and Statistics, University of Melbourne, Melbourne, Victoria, Australia

    Elisabeth Roesch & Michael P. H. Stumpf

  2. Melbourne Integrative Genomics, University of Melbourne, Melbourne, Victoria, Australia

    Elisabeth Roesch & Michael P. H. Stumpf

  3. JuliaHub, Somerville, MA, USA

    Elisabeth Roesch & Christopher Rackauckas

  4. Medical Research Council Laboratory of Molecular Biology, Cambridge, UK

    Joe G. Greener

  5. Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA

    Adam L. MacLean

  6. RelationalAI, Berkeley, CA, USA

    Huda Nassar

  7. Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA

    Christopher Rackauckas

  8. Pumas-AI, Centreville, VA, USA

    Christopher Rackauckas

  9. Departments of Neuroscience and Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA

    Timothy E. Holy

  10. School of BioSciences, The University of Melbourne, Melbourne, Victoria, Australia

    Michael P. H. Stumpf

  11. ARC Centre of Excellence for the Mathematical Analysis of Cellular Systems, Melbourne, Victoria, Australia

    Michael P. H. Stumpf

Authors
  1. Elisabeth Roesch
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  2. Joe G. Greener
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  3. Adam L. MacLean
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  4. Huda Nassar
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Contributions

E.R. and M.P.H.S. conceived of the concept of the project and were in charge of the overall direction and planning. All authors contributed to writing the manuscript and have read and approved the final version.

Corresponding author

Correspondence to Michael P. H. Stumpf.

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Competing interests

E.R. is a Sales Engineer at JuliaHub. C.R. is the Vice President of Modeling and Simulation at JuliaHub and Director of Scientific Research at Pumas-AI. T.E.H. is a steward of the Julia project. H.N. is a Senior Computer Scientist at RelationalAI. J.G.G., A.L.M. and M.P.H.S. declare no competing interests.

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Roesch, E., Greener, J.G., MacLean, A.L. et al. Julia for biologists. Nat Methods 20, 655–664 (2023). https://doi.org/10.1038/s41592-023-01832-z

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