Loïc Lannelongue

Nov 7, 2024 | nature.com | Loïc Lannelongue

A recent study has modeled and quantified the expected rise in electronic waste due to the increasing deployment of generative artificial intelligence.

Jan 26, 2024 | nature.com | Caroline Jay |Yurong Yu |Ian Crawford |Scott Archer-Nicholls |Loïc Lannelongue |Emily Lines

Artificial Intelligence (AI) and data science will play a crucial role in improving environmental sustainability, but the energy requirements of these methods will have an increasingly negative effect on the environment without sustainable design and use.

Aug 14, 2023 | biorxiv.org | Loïc Lannelongue |Michael Inouye

AbstractProtein-protein interactions (PPIs) are essential to understanding biological pathways as well as their roles in development and disease. Computational tools, based on classic machine learning, have been successful at predicting PPIs in silico, but the lack of consistent and reliable frameworks for this task has led to network models that are difficult to compare and discrepancies between algorithms that remain unexplained.

Mar 29, 2023 | nature.com | Yu Xu |Scott Ritchie |Maik Pietzner |Loïc Lannelongue |Samuel A. Lambert |Sebastian May-Wilson | +17 more

AbstractThe use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics1.

Feb 16, 2023 | nature.com | Loïc Lannelongue

Data analysis relies heavily on computation, and algorithms have grown more demanding in terms of hardware and energy. Monitoring their environmental impacts is and will continue to be an essential part of sustainable research. Here, we provide guidance on how to do so accurately and with limited overheads. The urgency for environmentally sustainable research practices has never been greater.