Author

Loïc Lannelongue

University of CambridgeORCID 0000-0002-9135-1345Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 3 Organism:human· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:database / resource· 1 Assay:GWAS summary statistics· 1 Approach:machine learning (classical)· 1 Assay:metabolomics· 1

Frequent Co-Authors

Michael InouyeiD· 3 shared Adam S. ButterworthiD· 1 shared Anders MälarstigiD· 1 shared Artika P. NathiD· 1 shared Åsa JohanssoniD· 1 shared Bram Peter PrinsiD· 1 shared Carles FoguetiD· 1 shared Christopher YauiD· 1 shared

Activity by Year

2022-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersBioinformatics

Michael InouyeORCID

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Author profile →

3 papers

Recent·Most cited

An atlas of genetic scores to predict multi-omic traits

Yu Xu, Scott C. Ritchie, Yujian Liang, Paul R. H. J. Timmers, Maik Pietzner, Loïc Lannelongue, Samuel A. Lambert, Usman A. Tahir, Sebastian May-Wilson, Carles Foguet, Åsa Johansson, Praveen Surendran, Artika P. Nath, Elodie Persyn, James E. Peters, , Michael Inouye

The paper develops genetic scores for 17,227 molecular traits using multi-omic data from INTERVAL and validates them across ancestries, demonstrating their utility in pathway analysis and disease association discovery.

Nature · Mar 29, 2023Peer-reviewedGenomics

Pitfalls of machine learning models for protein-protein interactions

Loïc Lannelongue, Michael Inouye

The paper benchmarks machine learning models for predicting protein-protein interactions, showing that functional genomics models outperform sequence-based ones and that algorithm design has little impact on performance with functional genomic data.

bioRxiv · Feb 7, 2022 · PreprintBioinformatics

The carbon footprint of bioinformatics

Jason Grealey, Loïc Lannelongue, Woei‐Yuh Saw, Jonathan Marten, Guillaume Méric, Sergio Ruiz Carmona, Michael Inouye

This study quantifies the carbon footprint of bioinformatics analyses and identifies strategies to reduce energy consumption and CO2 emissions.

Molecular Biology and Evolution · Feb 4, 2022Peer-reviewedBioinformatics