| Green Algorithms: Quantifying the Carbon Footprint of Computation L Lannelongue, J Grealey, M Inouye Advanced Science, 2021 | 320 | 2021 |
| The carbon footprint of bioinformatics J Grealey, L Lannelongue, WY Saw, J Marten, G Méric, S Ruiz-Carmona, ... Molecular biology and evolution 39 (3), msac034, 2022 | 65 | 2022 |
| An atlas of genetic scores to predict multi-omic traits Y Xu, SC Ritchie, Y Liang, PRHJ Timmers, M Pietzner, L Lannelongue, ... Nature 616 (7955), 123-131, 2023 | 47 | 2023 |
| Ten simple rules to make your computing more environmentally sustainable L Lannelongue, J Grealey, A Bateman, M Inouye PLoS Computational Biology 17 (9), e1009324, 2021 | 47 | 2021 |
| How to estimate carbon footprint when training deep learning models? A guide and review L Bouza, A Bugeau, L Lannelongue Environmental Research Communications 5 (11), 115014, 2023 | 29 | 2023 |
| GREENER principles for environmentally sustainable computational science L Lannelongue, HEG Aronson, A Bateman, E Birney, T Caplan, M Juckes, ... Nature Computational Science 3 (6), 514-521, 2023 | 25 | 2023 |
| Carbon footprint estimation for computational research L Lannelongue, M Inouye Nature Reviews Methods Primers 3 (1), 9, 2023 | 21 | 2023 |
| Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging NE Souter, L Lannelongue, G Samuel, C Racey, LJ Colling, N Bhagwat, ... Imaging Neuroscience 1, 1-15, 2023 | 5 | 2023 |
| Triplex doppler ultrasonography to describe the uterine arteries during diestrus and progesterone profile in pregnant and non-pregnant bitches of different sizes J Roos, C Aubanel, Z Niewiadomska, L Lannelongue, C Maenhoudt, ... Theriogenology 141, 153-160, 2020 | 4 | 2020 |
| Pitfalls of machine learning models for protein–protein interaction networks L Lannelongue, M Inouye Bioinformatics 40 (2), btae012, 2024 | 3* | 2024 |
| Carbon footprint: the (not so) hidden cost of high performance computing L Lannelongue ITNOW 63 (4), 12-13, 2021 | 3 | 2021 |
| Prioritize environmental sustainability in use of AI and data science methods C Jay, Y Yu, I Crawford, S Archer-Nicholls, P James, A Gledson, ... Nature Geoscience 17 (2), 106-108, 2024 | 2 | 2024 |
| Environmental Impacts of Machine Learning Applications in Protein Science L Lannelongue, M Inouye Cold Spring Harbor Perspectives in Biology 15 (12), a041473, 2023 | 2 | 2023 |
| Measuring and reducing the carbon footprint of fMRI preprocessing in fMRIPrep NE Souter, N Bhagwat, C Racey, R Wilkinson, NW Duncan, G Samuel, ... John Wiley & Sons, Inc., 2024 | 1 | 2024 |
| Inference frameworks in computational biology: from protein-protein interaction networks using machine learning to carbon footprint estimation. L Lannelongue | | 2023 |
| Gene Regulatory Networks to Explain Coronary Artery Disease Heritability M Inouye, L Lannelongue Journal of the American College of Cardiology 73 (23), 2958-2960, 2019 | | 2019 |
| Comparing the carbon footprint of fMRI data processing and analysis approaches NE Souter, C Racey, N Bhagwat, R Wilkinson, NW Duncan, G Samuel, ... OSF, 0 | | |
| Green Algorithms for Health Data Science L Lannelongue, J Grealey, M Inouye | | |
Michael InouyeProfessor of Systems Genomics & Population Health, University of Cambridge; Baker Institute在 medschl.cam.ac.uk 的电子邮件经过验证
