Author

Frances M. G. Pearl

University of SussexORCID 0000-0002-8210-4393Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:differential expression· 2 Organism:human· 2 Assay:proteomics· 2 Assay:bulk RNA-seq· 1 Assay:CRISPR screen· 1 Research Focus:database / resource· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Sarah K. Wooller· 2 shared Aikaterini AnagnostopoulouiD· 1 shared Antony M. CarriD· 1 shared Benno KuropkaiD· 1 shared Graeme Benstead-HumeiD· 1 shared György KemenesiD· 1 shared Ildikó KemenesiD· 1 shared Joanna RenautiD· 1 shared

Activity by Year

2022-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersBioinformatics

Sarah K. Wooller

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3 papers

Recent·Most cited

BioinformaticsBioinformaticsPeer-reviewedMay 27, 2026

Using Cancer Profiles to Identify Synthetic Lethal Therapeutic Targets and Predictive Biomarkers in Cancer Gene Dependency Data

Laurence H. Pearl, Frances M. G. Pearl

DepMine identifies synthetic lethal relationships and predictive biomarkers in cancer gene dependency data by integrating genetic profiles and dependency data.

DOI 10.1093/bioinformatics/btag337

humanCRISPR screen

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BioinformaticsJournal of Experimental BiologyPeer-reviewedApr 1, 2022

A combined bioinformatics and LC-MS based approach for the development and benchmarking of a comprehensive database for CNS proteins in Lymnaea stagnalis

Sarah K. Wooller, Aikaterini Anagnostopoulou, Benno Kuropka…·Murat Eravci

The paper develops and benchmarks a comprehensive CNS proteomics database for Lymnaea stagnalis using bioinformatics and LC-MS proteomics, identifying more proteins than a non-specific database.

5 citations

mouseproteomics

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Systems BiologyBioinformatics AdvancesPeer-reviewedJan 1, 2022

Biological network topology features predict gene dependencies in cancer cell lines

Graeme Benstead-Hume, Sarah K. Wooller, Joanna Renaut…·Frances M. G. Pearl

The paper predicts cell line-specific acquired essential genes using perturbed PPI networks and machine learning, achieving AUC ROC scores of 0.75-0.85.

6 citations

humanproteomics

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