Author

Riku Turkki

AstraZeneca (Sweden)ORCID 0000-0002-8690-6983Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:deep learning· 2 Assay:imaging· 2 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Carola‐Bibiane SchönliebiD· 1 shared Charles-Hugues Lardeau· 1 shared Elizabeth MouchetiD· 1 shared Erik MüllersiD· 1 shared Guy B. WilliamsiD· 1 shared Jan Cross-ZamirskiiD· 1 shared Johan Fredin HaslumiD· 1 shared Johan KarlssoniD· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperBioinformatics

Carola‐Bibiane SchönliebORCID

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2 papers

Recent·Most cited

Cell Painting-based bioactivity prediction boosts high-throughput screening hit-rates and compound diversity

Johan Fredin Haslum, Charles-Hugues Lardeau, Johan Karlsson, Riku Turkki, Karl‐Johan Leuchowius, Kevin Smith, Erik Müllers

This study uses deep learning on Cell Painting data to predict compound bioactivity, improving hit rates and diversity in high-throughput screening.

Nature Communications · Apr 24, 2024Peer-reviewedBioinformatics

Label-free prediction of Cell Painting from brightfield images

Jan Cross-Zamirski, Elizabeth Mouchet, Guy B. Williams, Carola‐Bibiane Schönlieb, Riku Turkki, Yinhai Wang

This study predicts fluorescent Cell Painting images from brightfield images using deep learning, achieving high correlation and demonstrating potential for downstream analysis and repurposing imaging channels.

Scientific Reports · Jun 15, 2022Peer-reviewedBioinformatics