Green algorithms: quantifying the carbon footprint of computation L Lannelongue, J Grealey, M Inouye Advanced science 8 (12), 2100707, 2021 | 248 | 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 | 57 | 2022 |
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 | 37 | 2021 |
Machine learning optimized polygenic scores for blood cell traits identify sex-specific trajectories and genetic correlations with disease Y Xu, D Vuckovic, SC Ritchie, P Akbari, T Jiang, J Grealey, AS Butterworth, ... Cell Genomics 2 (1), 2022 | 19* | 2022 |
A proteomic-based prognostic signature of pancreatic adenocarcinoma AT Aref, AKM Azad, A Anees, M Pathan, J Grealey, DL Smith, ... Cancer Research 83 (7_Supplement), 2209-2209, 2023 | | 2023 |
Deep Learning Approaches for Genomic Prediction and Quantifying Computational Carbon Footprints JG Grealey La Trobe, 2021 | | 2021 |
Green Algorithms for Health Data Science L Lannelongue, J Grealey, M Inouye | | |