Added GREENER publication

Author: Llannelongue

_pages/publications.md

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 ### 2023
 
-- L. Lannelongue and M. Inouye, [‘Carbon footprint estimation for computational research’](https://rdcu.be/c5KPJ), _Nat Rev Methods Primers_, vol. 3, no. 1, Art. no. 1, Feb. 2023, doi: 10.1038/s43586-023-00202-5.
+- ['GREENER principles for environmentally sustainable computational science'](https://rdcu.be/dfpLM), L. Lannelongue, H.-E. G. Aronson, A. Bateman, E. Birney, T. Caplan, M. Juckes, J. McEntyre, A. D. Morris, G. Reilly and M. Inouye, _Nat Comput Sci_, vol. 3, no. 6, pp. 514–521, Jun. 2023, doi: 10.1038/s43588-023-00461-y.
+- ['Carbon footprint estimation for computational research'](https://rdcu.be/c5KPJ), L. Lannelongue and M. Inouye, _Nat Rev Methods Primers_, vol. 3, no. 1, Art. no. 1, Feb. 2023, doi: 10.1038/s43586-023-00202-5.
 [\[pdf\]]({% link assets/publications/2023_Comment_NRPM.pdf %})
 
 
 ### 2022
 
-- L. Grealey, L. Lannelongue., W.-Y. Saw, J. Marten, G. Méric, S. Ruiz-Carmona and M. Inouye, [‘The Carbon Footprint of Bioinformatics’](https://academic.oup.com/mbe/article/39/3/msac034/6526403), _Molecular Biology and Evolution_, p. msac034, Feb. 2022, doi: 10.1093/molbev/msac034.
+- ['The Carbon Footprint of Bioinformatics'](https://academic.oup.com/mbe/article/39/3/msac034/6526403), L. Grealey, L. Lannelongue., W.-Y. Saw, J. Marten, G. Méric, S. Ruiz-Carmona and M. Inouye, _Molecular Biology and Evolution_, p. msac034, Feb. 2022, doi: 10.1093/molbev/msac034.
 [\[pdf\]]({% link assets/publications/2022_Carbon-Footprint-of-bioinformatics.pdf %})
-- L. Lannelongue, [‘Carbon footprint: the (not so) hidden cost of high performance computing’](https://www.bcs.org/articles-opinion-and-research/carbon-footprint-the-not-so-hidden-cost-of-high-performance-computing/), _ITNOW_, vol. 63, no. 4, pp. 12–13, Jan. 2022, doi: 10.1093/itnow/bwab100.
+- [‘Carbon footprint: the (not so) hidden cost of high performance computing’](https://www.bcs.org/articles-opinion-and-research/carbon-footprint-the-not-so-hidden-cost-of-high-performance-computing/), L. Lannelongue, _ITNOW_, vol. 63, no. 4, pp. 12–13, Jan. 2022, doi: 10.1093/itnow/bwab100.
 [\[pdf\]]({% link assets/publications/2022_hidden-cost-of-HPC_ITNOW.pdf %})
 
 
 ### 2021
 
-- L. Lannelongue, J. Grealey, and M. Inouye, ['Green Algorithms: Quantifying the Carbon Footprint of Computation'](https://doi.org/10.1002/advs.202100707), _Advanced Science_, vol. 8, no. 12, p. 2100707, July 2021, doi: 10.1002/advs.202100707.
+- ['Green Algorithms: Quantifying the Carbon Footprint of Computation'](https://doi.org/10.1002/advs.202100707), L. Lannelongue, J. Grealey, and M. Inouye, _Advanced Science_, vol. 8, no. 12, p. 2100707, July 2021, doi: 10.1002/advs.202100707.
 [\[pdf\]]({% link assets/publications/2021_Green Algorithms_AdvScience.pdf %})
-- L. Lannelongue, J. Grealey, A. Bateman, and M. Inouye, [‘Ten simple rules to make your computing more environmentally sustainable’](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009324), _PLoS Computational Biology_, vol. 17, no. 9, p. e1009324, Sept. 2021, doi: 10.1371/journal.pcbi.1009324.
+- [‘Ten simple rules to make your computing more environmentally sustainable’](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009324),L. Lannelongue, J. Grealey, A. Bateman, and M. Inouye, _PLoS Computational Biology_, vol. 17, no. 9, p. e1009324, Sept. 2021, doi: 10.1371/journal.pcbi.1009324.
 [\[pdf\]]({% link assets/publications/2021_10-simple-rules_PLOScompbio.pdf %})
 
 ### 2020
 
-- M. Inouye, L. Lannelongue and J. Grealey, [Green Algorithms for Health Data Science](https://www.hdruk.org/news/green-algorithms-for-health-data-science/), _HDR UK Blog_, Mar. 2020.
+- [Green Algorithms for Health Data Science](https://www.hdruk.org/news/green-algorithms-for-health-data-science/), M. Inouye, L. Lannelongue and J. Grealey, _HDR UK Blog_, Mar. 2020.

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+last_modified_at: 07/07/2023
 
 
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 <!-- __:hourglass: This website is a work in progress, and we will keep adding content in the coming weeks/months!__ Comments/suggestions can be made [here](https://github.com/GreenAlgorithms/GreenAlgorithms.github.io/issues).
 {: .notice--warning} -->
 
-__:mega: New publication! _"Carbon footprint estimation for computational research".___ We have just released a Comment in _Nature Reviews Methods Primers_ that summarises the different ways you can estimate the environmental impacts of your algorithms. [\[link\]](https://www.nature.com/articles/s43586-023-00202-5) [\[pdf\]]({% link assets/publications/2023_Comment_NRPM.pdf %})
+__:mega: New publication! _"GREENER principles for environmentally sustainable computational science".___ We have just released a Perspective in _Nature Computational Science_ which sets out fundamental principles for environmentally sustainable computational science (acronym GREENER), as well as guidance for best practices moving forward. The work was a collaboration with major stakeholders such as HDR-UK, EMBL-EBI, Wellcome and UKRI. [\[link\]](https://rdcu.be/dfpLM)
+<!-- {% include figure image_path="assets/images/roadmap figures 8b.jpg" %} -->
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 The Green Algorithms project aims at promoting more environmentally sustainable computational science. It regroups calculators that researchers can use to estimate the carbon footprint of their projects, tips on how to be more environmentally friendly, training material, past talks etc.